Insight into user experience and behavior is critical to the success of large software systems and web services. Gaining such insights, while preserving user privacy, is a significant challenge. Recent advancements in multi-party computation have made it practical to securely compute aggregates over secret shared data. Two such protocols have emerged as candidates for standardization at the IETF: Prio (NSDI 2017) for general-purpose statistics; and Poplar (IEEE S&P 2021) for heavy hitters, where the goal is to compute the most popular inputs held by users without learning the inputs themselves. While each of these protocols is well-suited to certain applications, there remain a number of use cases identified by IETF for which neither Prio nor Poplar is practical. We introduce Mastic, a protocol for the following functionality: each of a large number of clients holds an input (e.g., a URL) and its corresponding weight (e.g., page load time); for a given candidate input (or prefix), a small number of non-colluding servers wish to securely aggregate the weights of clients that hold that input (or some input with that prefix), without learning the weights or which client holds which input. This functionality makes two new classes of applications possible. The first is a natural generalization of heavy hitters we call weighted heavy-hitters. The second is an enhancement of Prio-style metrics we call attribute-based metrics in which aggregates are grouped by hierarchical user attributes (e.g., their geographic location or software version). We demonstrate Mastic's practicality for these applications with a real-world example of each. We also compare our protocol with Prio and Poplar on a wide area network. Overall, we report over one order of magnitude performance improvement over Poplar for plain heavy-hitters and $1.5-2\times$ improvement over Prio for attribute-based metrics.

We propose plausible post-quantum (PQ) oblivious pseudorandom functions (OPRFs) based on the Power-Residue PRF (Damgård CRYPTO’88), a generalization of the Legendre PRF. For security parameter $\lambda$, we consider the PRF $\mathsf{Gold}_k(x)$ that maps an integer $x$ modulo a public prime $p = 2^\lambda\cdot g + 1$ to the element $(k + x)^g \bmod p$, where $g$ is public and $\log g \approx 2\lambda$. At the core of our constructions are efficient novel methods for evaluating $\mathsf{Gold}$ within two-party computation ($\mathsf{2PC}\text{-}\mathsf{Gold}$), achieving different security requirements. Here, the server $\mathcal{P}_s$ holds the PRF key $k$ whereas the client $\mathcal{P}_c$ holds the PRF input $x$, and they jointly evaluate $\mathsf{Gold}$ in 2PC. $\mathsf{2PC}\text{-}\mathsf{Gold}$ uses standard Vector Oblivious Linear Evaluation (VOLE) correlations and is information-theoretic and constant-round in the (V)OLE-hybrid model. We show: • For a semi-honest $\mathcal{P}_s$ and a malicious $\mathcal{P}_c$: a $\mathsf{2PC}\text{-}\mathsf{Gold}$ that just uses a single (V)OLE correlation, and has a communication complexity of $3$ field elements ($2$ field elements if we only require a uniformly sampled key) and a computational complexity of $\mathcal{O}(\lambda)$ field operations. We refer to this as half-malicious security. • For malicious $\mathcal{P}_s$ and $\mathcal{P}_c$: a $\mathsf{2PC}\text{-}\mathsf{Gold}$ that just uses $\frac{\lambda}{4} + \mathcal{O}(1)$ VOLE correlations, and has a communication complexity of $\frac{\lambda}{4} + \mathcal{O}(1)$ field elements and a computational complexity of $\mathcal{O}(\lambda)$ field operations. These constructions support additional features and extensions, e.g., batched evaluations with better amortized costs where $\mathcal{P}_c$ repeatedly evaluates the PRF under the same key. Furthermore, we extend $\mathsf{2PC}\text{-}\mathsf{Gold}$ to Verifiable OPRFs and use the methodology from Beullens et al. (ePrint’24) to obtain strong OPRF security in the universally composable setting. All the protocols are efficient in practice. We implemented $\mathsf{2PC}\text{-}\mathsf{Gold}$—with (PQ) VOLEs—and benchmarked them. For example, our half-malicious (resp. malicious) $n$-batched PQ OPRFs incur about $100$B (resp. $1.9$KB) of amortized communication for $\lambda = 128$.

A dot-product proof (DPP) is a simple probabilistic proof system in which the input statement $\mathbf{x}$ and the proof $\boldsymbol{\pi}$ are vectors over a finite field $\mathbb{F}$, and the proof is verified by making a single dot-product query $\langle \mathbf{q},(\mathbf{x} \| \boldsymbol{\pi}) \rangle$ jointly to $\mathbf{x}$ and $\boldsymbol{\pi}$. A DPP can be viewed as a 1-query fully linear PCP. We study the feasibility and efficiency of DPPs, obtaining the following results: - Small-field DPP. For any finite field $\mathbb{F}$ and Boolean circuit $C$ of size $S$, there is a DPP for proving that there exists $\mathbf{w}$ such that $C(\mathbf{x}, \mathbf{w})=1$ with a proof $\boldsymbol{\pi}$ of length $S\cdot\mathsf{poly}(|\mathbb{F}|)$ and soundness error $\varepsilon=O(1 / \sqrt{|\mathbb{F}|})$. We show this error to be asymptotically optimal. In particular, and in contrast to the best known PCPs, there exist strictly linear-length DPPs over constant-size fields. - Large-field DPP. If $|\mathbb{F}|\ge\mathsf{poly}(S/\varepsilon)$, there is a similar DPP with soundness error $\varepsilon$ and proof length $O(S)$ (in field elements). The above results do not rely on the PCP theorem and their proofs are considerably simpler. We apply our DPP constructions toward two kinds of applications. - Hardness of approximation. We obtain a simple proof for the NP-hardness of approximating MAXLIN (with dense instances) over any finite field $\mathbb{F}$ up to some constant factor $c>1$, independent of $\mathbb{F}$. Unlike previous PCP-based proofs, our proof yields exponential-time hardness under the exponential time hypothesis (ETH). - Succinct arguments. We improve the concrete efficiency of succinct interactive arguments in the generic group model using input-independent preprocessing. In particular, the communication is comparable to sending two group elements and the verifier's computation is dominated by a single group exponentiation. We also show how to use DPPs together with linear-only encryption to construct succinct commit-and-prove arguments.

Cryptographic protocols such as zk-SNARKs use 2-cycles of~elliptic curves for efficiency, often relying on pairing computations. However, 2-cycles of~pairing-friendly curves are hard to find, and the only known cases consist of~an MNT4 and an MNT6 curve. In this work, we prove that a~2-cycle containing an MNT3, Freeman, or BN curve cannot be pairing-friendly. Thus we cannot hope to find new pairing-friendly 2-cycles using the current methods. Furthermore, we show that there are no SNARK-friendly 2-chains of elliptic curves from combinations of MNT, Freeman and BN curves of reasonable size, except for (MNT4, MNT6).

We provide several attacks on the BASS signature scheme introduced by Grigoriev, Ilmer, Ovchinnikov and Shpilrain in 2023. We lay out a trivial forgery attack which generates signatures passing the scheme's probabilistic signature verification with high probability. Generating these forgeries is faster than generating signatures honestly. Moreover, we describe a key-only attack which allows us to recover an equivalent private key from a signer's public key. The time complexity of this recovery is asymptotically the same as that of signing messages.

Since the selection of the National Institute of Standards and Technology (NIST) Post-Quantum Cryptography (PQC) standardization algorithms, research on integrating PQC into security protocols such as TLS/SSL, IPSec, and DNSSEC has been actively pursued. However, PQC migration for Internet of Things (IoT) communication protocols remains largely unexplored. Embedded devices in IoT environments have limited computational power and memory, making it crucial to optimize PQC algorithms for efficient computation and minimal memory usage when deploying them on low-spec IoT devices. In this paper, we introduce KEM-MQTT, a lightweight and efficient Key Encapsulation Mechanism (KEM) for the Message Queuing Telemetry Transport (MQTT) protocol, widely used in IoT environments. Our approach applies the NIST KEM algorithm Crystals-Kyber (Kyber) while leveraging MQTT’s characteristics and sensor node constraints. To enhance efficiency, we address certificate verification issues and adopt KEMTLS to eliminate the need for Post-Quantum Digital Signatures Algorithm (PQC-DSA) in mutual authentication. As a result, KEM-MQTT retains its lightweight properties while maintaining the security guarantees of TLS 1.3. We identify inefficiencies in existing Kyber implementations on 8-bit AVR microcontrollers (MCUs), which are highly resource-constrained. To address this, we propose novel implementation techniques that optimize Kyber for AVR, focusing on high-speed execution, reduced memory consumption, and secure implementation, including Signed LookUp-Table (LUT) Reduction. Our optimized Kyber achieves performance gains of 81%,75%, and 85% in the KeyGen, Encaps, and DeCaps processes, respectively, compared to the reference implementation. With approximately 3 KB of stack usage, our Kyber implementation surpasses all state-of-the-art Elliptic Curve Diffie-Hellman (ECDH) implementations. Finally, in KEM-MQTT using Kyber-512, an 8-bit AVR device completes the handshake preparation process in 4.32 seconds, excluding the physical transmission and reception times.

Private Join and Compute (PJC) is a two-party protocol recently proposed by Google for various use-cases, including ad conversion (Asiacrypt 2021) and which generalizes their deployed private set intersection sum (PSI-SUM) protocol (EuroS&P 2020). PJC allows two parties, each holding a key-value database, to privately evaluate the inner product of the values whose keys lie in the intersection. While the functionality output is not typically considered in the security model of the MPC literature, it may pose real-world privacy risks, thus raising concerns about the potential deployment of protocols like PJC. In this work, we analyze the risks associated with the PJC functionality output. We consider an adversary that is a participating party of PJC and describe four practical attacks that break the other party's input privacy, and which are able to recover both membership of keys in the intersection and their associated values. Our attacks consider the privacy threats associated with deployment and highlight the need to include the functionality output as part of the MPC security model.

We present a new generalization of (zk-)SNARKs specifically designed for the application domain of safety-critical control systems. These need to be protected against adversarial tampering as well as non-malicious but unintended system failures due to random faults in components. Our SNARKs combine two additional features at the same time. Besides the verification of correct computation, they also allow, first, the verification of input data authenticity. Specifically, a verifier can confirm that the input to the computation originated from a trusted source. Second, our SNARKs support verification of stateful computations across multiple rounds, ensuring that the output of the current round correctly depends on the internal state of the previous round. Our focus is on concrete practicality, so we abstain from arithmetizing hash functions or signatures in our SNARKs. Rather, we modify the internals of an existing SNARK to extend its functionality. We implement and benchmark our new SNARKs in a sample scenario of a real-time high-integrity flight control system. With our construction, prover runtime improves significantly over the baseline by a factor of 90. Verification time increases by 36%, but is less than comparable approaches that do not arithmetize hash functions or signatures.

Homomorphic message authentication codes (HMACs) allow users to authenticate data using a shared secret key, while supporting computation over authenticated data. Given data $(m_1, \ldots, m_n)$ and their tags $(\sigma_1, \ldots, \sigma_n)$, anyone can evaluate a circuit $C$ on the data and tags to produce a succinct tag authenticating the output $C(m_1, \ldots, m_n)$. Importantly, tags remain succinc -- of size polynomial in the security parameter $\lambda$ -- regardless of the size of $C$. This work introduces an enhanced variant of HMACs called algebraic HMAC (aHMAC), in which all tags (input and output) take the form $\Delta \cdot m + K$, as in standard information-theoretic MACs. We construct an aHMAC from group-based assumptions, including variants of the DDH and DCR assumptions, and use it to obtain group-based constructions of several cryptographic primitives: - Succinct CDS for circuits. For any $P: [N]^k \to [N]$ represented by circuit, we obtain a Conditional Disclosure of Secrets protocol with poly$(\lambda, k, \log N )$ communication. - Succinct PSM for simple programs. For any $P:[N]^k \to [N]$ represented by a truth-table or shallow branching program, we obtain a Private Simultaneous Messages protocol or a garbling scheme with poly$(\lambda, k, \log N )$ communication. - Constrained PRFs for circuits. We obtain the first group-based constrained pseudorandom functions for general circuits, improving over a previous construction for NC1 circuits. Prior to our work, these applications could only be obtained from lattice assumptions or indistinguishability obfuscation.

Homomorphic encryption (HE) is a foundational technology in privacy-enhancing cryptography, enabling computation over encrypted data. Recently, generalized HE primitives designed for multi-party applications, such as multi-party HE (MPHE), have garnered significant research interest. While constructing secure multi-party protocols from MPHE in the semi-honest model is straightforward, achieving malicious security remains challenging as it requires zero-knowledge arguments of knowledge (ZKAoKs) for MPHE ciphertexts and public keys. In this work, we design practical ZKAoKs for MPHE that validate the well-formedness of public keys and ciphertexts. Specifically, we develop our ZKAoKs within the polynomial interactive oracle proof (PIOP) framework. To achieve this, we introduce novel optimization techniques that seamlessly integrate constraints for MPHE into the PIOP framework, enabling the design of PIOPs for validating all types of MPHE public keys, including relinearization and automorphism keys. To the best of our knowledge, our construction is the first ZKAoK for MPHE that validates automorphism keys. We instantiate our PIOP using a lattice-based polynomial commitment scheme (PCS). When compared with the previous state-of-the-art construction, PELTA (CCS' 2023), our implementation achieves a 5.4x reduction in proof size, a 111x speed-up in proof generation, and a 768x improvement in verification time for validating the encryption key. In addition to the encryption key, we provide benchmark results for all types of ZKAoKs required for MPHE, presenting the first concrete performance results in compiling passively secure MPHE-based protocols into maliciously secure ones.

Distributed randomness beacon protocols, which continuously generate publicly verifiable randomness values, are crucial for many applications. Publicly verifiable secret sharing (PVSS) scheme is a promising cryptographic primitive for implementing beacon protocols, such as Hydrand (S\&P'20), SPURT (S\&P'22), OptRand (NDSS'23) and GRandLine (CCS'24). However, two key challenges remain unresolved: asynchrony and reconfiguration. In this paper, we introduce the $AsyRand$ beacon protocol to address these challenges. First, we incorporate a producer-consumer model to decouple the production and consumption of PVSS commitments, which are managed using first-in first-out (FIFO) queues. Parties utilize reliable broadcast (RBC) to produce PVSS commitments independently. Meanwhile, they collectively consume each commitment (i.e., recover the underlying secret) applying a $t$-validated asynchronous Byzantine agreement ($t$-VABA) protocol. Then, each beacon randomness value is delivered given a PVSS secret is recovered. Moreover, each party enables to detect potential faults of other parties by locally monitoring the queue states. If the queue of some party keeps empty for long, the party is considered faulty and others can initiate to remove it in a removal process. Also, a new party can request to participate in via a joining process without system restart. As an independent contribution, we propose a novel PVSS scheme based on the Sigma protocol and Fiat-Shamir heuristic. Regarding complexity, $AsyRand$ achieves state-of-the-art performance with $O(n^2)$ communication complexity, $O(n)$ computation complexity, and $O(n)$ verification complexity. Experimental results highlight the performance of $AsyRand$ compared to related works.

The Estonian i-voting experience is probably the richest to analyze; a country that is considered a pioneer in digitizing both the government and private sector since 2001, and hence digital voting in 2005, yet there are still some complaints submitted, critics and remarks to consider about the IVXV system. In this paper, we introduce a Systemization of Knowledge of the Estonian IVXV i-voting system and propose some added security enhancements. The presented SoK includes applications implemented by election observers in 2023 & 2024 elections, which, to our knowledge, has never been mentioned and/or analyzed in the academia before. The paper also updates the general knowledge about an extra right given to auditors (but not observers) in the June 2024 European election, recent improvements, and recent complaints. Finally, we discuss the current system status in 2024 EP elections, propose our own suggestions to some remaining vulnerabilities, then raise the inevitable question of the approaching quantum threat.

We present Bitcoin Thunderbolt, a novel off-chain protocol for asynchronous, secure transfer of Bitcoin UTXOs between uncoordinated users. Unlike prior solutions such as payment channels or the Lightning Network, Bitcoin Thunderbolt requires no prior trust, direct interaction, or continuous connectivity between sender and receiver. At its core, Bitcoin Thunderbolt employs a Byzantine fault-tolerant committee to manage threshold Schnorr signatures, enabling secure ownership delegation and on-chain finalization. Our design supports recursive, off-chain UTXO transfers using tweakable, verifiable signature components. The protocol tolerates up to $f$ malicious nodes in a $3f+1$ committee and ensures correctness, consistency, and one-time spendability under asynchronous network conditions. We formally verify Bitcoin Thunderbolt’s key security properties, namely, unforgeability, ownership soundness, and liveness—using the Tamarin prover. Our results demonstrate that Thunderbolt provides robust, scalable, and non-interactive off-chain Bitcoin transfers, significantly expanding the practical utility of Bitcoin for decentralized applications.

Succinct Non-Interactive Arguments of Knowledge (SNARKs) provide a powerful cryptographic framework enabling short, quickly verifiable proofs for computational statements. Existing SNARKs primarily target computations represented as arithmetic circuits. However, they become inefficient when handling binary operations, as each gates operates on a few bits while still incurring the cost of multiple field operations per gate. This inefficiency stems, in part, from their inability to capture the word-level operations that are typical in real-world programs. To better reflect this computational pattern, we shift our attention to data-parallel boolean circuits, which serve as a natural abstraction of word-level operations by allowing parallel munipulation of multiple bits. To precisely characterize the prover's overheads in our scheme, we adopt the word RAM model, which aligns with the nature of modern programming languages. Under this model, we propose a novel approach to achieve SNARKs with only sub-linear prover overhead for proving boolean circuits. Specifically, we present an optimized GKR protocol for boolean circuits that captures the word-level operations. To achieve this, we pack multiple bits as a single univariate polynomial, and exploiting the binary nature of circuit values to enable precomputation to accelerate the sumcheck process. This optimization leads to a highly efficient prover requiring only sub-linear RAM operations. Furthermore, we introduce a sub-linear polynomial commitment scheme designed specifically for binary polynomials, which ensures efficient commitments with minimal computational overhead. Comprehensive evaluations reveal that our scheme achieves both theoretical efficiency and substantial practical performance gains. For instance, in proving randomly generated Boolean circuits with $2^{30}$ gates, proof generation with our optimized GKR protocol completes in just 5.38 seconds, yielding a $223\times$ speedup over LogUp (Haböck, ePrint 2022), the most efficient known scheme for lookup arguments. Furthermore, in an end-to-end benchmark over the Keccak-$f$ task, our scheme achieves a $106\times$ speedup compared to Binius (Diamond et al., EUROCRYPT 2025), the state-of-the-art work for boolean circuits.

We consider the problem of actively secure two-party machine-learning inference in the preprocessing model, where the parties obtain (input-independent) correlated randomness in an offline phase that they can then use to run an efficient protocol in the (input-dependent) online phase. In this setting, the state-of-the-art is the work of Escudero et al. (Crypto 2020); unfortunately, that protocol requires a large amount of correlated randomness, extensive communication, and many rounds of interaction, which leads to poor performance. In this work, we show protocols for this setting based on function secret sharing (FSS) that beat the state-of-the-art in all parameters: they use less correlated randomness and fewer rounds, and require lower communication and computation. We achieve this in part by allowing for a mix of boolean and arithmetic values in FSS-based protocols (something not done in prior work), as well as by relying on “interactive FSS,” a generalization of FSS we introduce. To demonstrate the effectiveness of our approach we build SHARK—the first FSS- based system for actively secure inference—which outperforms the state-of-the-art by up to 2300×.

The SPDZ protocol family is a popular choice for secure multi-party computation (MPC) in a dishonest majority setting with active adversaries. Over the past decade, a series of studies have focused on improving its offline phase, where special additive shares called authenticated triples are generated. However, to accommodate recent demands for matrix operations in secure machine learning and big integer arithmetic in distributed RSA key generation, updates to the offline phase are required. In this work, we propose a new protocol for the SPDZ offline phase, MatriGear, which improves upon the previous state-of-the-art construction, TopGear (Baum et al., SAC '19), and its variant for matrix triples (Chen et al., Asiacrypt '20). Our protocol aims to achieve a speedup in matrix triple generation and support for larger prime fields up to 4096 bits in size. To achieve this, we devise a variant of the BFV scheme and a new homomorphic matrix multiplication algorithm optimized for our purpose. As a result, our protocol achieves about 3.6x speedup for generating scalar triples in a 1024-bit prime field and about 34x speedup for generating 128x128 matrix triples. In addition, we reduce the size of evaluation keys from 27.4 GB to 0.22 GB and the communication cost for MAC key generation from 816 MB to 16.6 MB.

Dependence on online infrastructure is rapidly growing as services like online payments and insurance replace traditional options, while others, like social networks, offer new capabilities. The centralized service operators wield unilateral authority over user conflicts, content moderation, and access to essential services. In the context of payments, blockchains provide a decentralized alternative. They also enable decentralized execution of stateful programs called smart contracts. But those lack the contextual understanding and interpretative capabilities that would enable reasoning about complex scenarios. Advancements in machine learning (ML) are raising interest in actually-smart contracts, but blockchain computation constraints prohibit direct ML inference execution. While many projects deploy computation delegation mechanisms, they lack Turing-completeness, prohibit parallel computation, or suffer from high overhead. We present Arbigraph, a blockchain-based execution delegation protocol. Like previous optimistic solutions, the parties submit their computation results, allowing a smart contract to arbitrate in case of dispute. But Arbigraph employs a novel dual-graph data structure and takes advantage of the nature of the dispute process to achieve Turing completeness, constant-time memory access, and parallel execution. We formalize the problem and show that Arbigraph guarantees completeness, soundness, and progress. Experiments on LLM inference as well as matrix multiplication, which is at the core of ML inference, demonstrate that parallelization speedup grows linearly with matrix dimensions. We demonstrate Arbigraph's practical cost with a deployment on the Avalanche blockchain. Arbigraph thus enables decentralized, context-aware decision-making and unlocks unprecedented use cases for blockchains.

Byzantine atomic broadcast (ABC) is at the heart of permissioned blockchains and various multi-party computation protocols. We resolve a long-standing open problem in ABC, presenting the first information-theoretic (IT) and signature-free asynchronous ABC protocol that achieves optimal $O(n^2)$ messages and $O(1)$ expected time. Our ABC protocol adopts a new design, relying on a reduction from---perhaps surprisingly---a somewhat neglected primitive called multivalued Byzantine agreement (MBA).

The Updatable Signature (US) allows valid signatures to be updated by an update token without accessing the newly generated signing key. Cini et al. (PKC'21) formally defined this signature and gave several constructions. However, their security model requires the secrecy of the update token, which is only applicable in some specific scenarios, such as software verification in the trusted App Store. In Web3, information is usually shared via a public blockchain, and decentralized private computation is expensive. In addition, one can use the same token to update both the signing key and signatures and all signatures can be updated with a single token. The adversarial signature generated by an adversary might also be updated. Therefore, this work explores the (im)possibility of constructing an Updatable Signature with public tokens (USpt), the tokens of which are signature-dependent. Specifically, we define the updatable signature with public tokens and present its security model. Then, we present a concrete USpt scheme based on the Boneh–Lynn–Shacham signature. This variant introduces a limitation for the signer who must maintain a dataset about its signed messages or hashes of them, which is applicable in our applications.

In this paper, we focus on SM4, a widely used and standardized Chinese block cipher. After revisiting the previously proposed optimal 19-round differential characteristic, we observe that its applicability in differential attacks is limited by a reduced pre-sieving probability, causing the time complexity to exceed that of brute force. To overcome this issue, we employ an automated search approach to identify more promising optimal 19-round differential characteristics. By translating key properties relevant to key recovery into Boolean expressions, we uncover three structural properties common to all optimal 19-round characteristics. While these properties dictate the overall probability of the resulting 19-round distinguishers, their varying pre-sieving probabilities influence their practical effectiveness in differential attacks. Using Boolean encodings, we identify four representative key-recovery-friendly differential characteristics. We then conduct an in-depth analysis of one such characteristic and demonstrate that, when evaluated under both the hypothesis testing paradigm and the key ranking paradigm, the proposed attack requires slightly more data than existing 23-round attacks. Nonetheless, it achieves lower time and memory complexities and ensures a higher success probability, offering a valuable new avenue for differential cryptanalysis of SM4. We believe our findings enhance the understanding of SM4's differential structure and provide a solid foundation for future research on advanced key-recovery techniques that leverage these newly identified structural properties and differential characteristics.

In the usual syntax of digital signatures, the verification algorithm takes a verification key in addition to a signature and a message, whereas in ECDSA with key recovery, which is used in Ethereum, no verification key is input to the verification algorithm. Instead, a verification key is recovered from a signature and a message. In this paper, we explore BUFF security of ECDSA with key recovery (KR-ECDSA), where BUFF stands for Beyond UnForgeability Features (Cremers et al., IEEE S&P 2021). As a result, we show that KR-ECDSA provides BUFF security, except weak non-resignability (wNR). We pay attention to that the verification algorithm of KR-ECDSA takes an Ethereum address addr as input, which is defined as the rightmost 160-bits of the Keccak-256 hash of the corresponding ECDSA verification key, and checks the hash value of the recovered verification key is equal to addr. Our security analysis shows that this procedure is mandatory to provide BUFF security. We also discuss whether wNR is mandatory in Ethereum or not. To clarify the above equality check is mandatory to provide BUFF security in KR-ECDSA, we show that the original ECDSA does not provide any BUFF security. As a by-product of the analysis, we show that one of our BUFF attacks also works against the Aumayr et al.'s ECDSA-based adaptor signature scheme (ASIACRYPT 2021) and the Qin et al.'s blind adaptor signature scheme (IEEE S&P 2023), which is based on the Aumayr et al.'s scheme. We emphasize that the attack is positioned outside of their security models.

In this paper we present RevoLUT, a library implemented in Rust that reimagines the use of Look-Up-Tables (LUT) beyond their conventional role in function encoding, as commonly used in TFHE's programmable boostrapping. Instead, RevoLUT leverages LUTs as first class objects, enabling efficient oblivious operations such as array access, elements sorting and permutation directly within the table. This approach supports oblivious algortithm, providing a secure, privacy-preserving solution for handling sensitive data in various applications.

In this paper, we introduce an adaptation of the counting sort algorithm that leverages the data obliviousness of the algorithm to enable the sorting of encrypted data using Fully Homomorphic Encryption (FHE). Our approach represents the first known sorting algorithm for encrypted data that does not rely on comparisons. The implementation takes advantage of some basic operations on TFHE's Look-Up-Tables (LUT). We have integrated these operations into RevoLUT, a comprehensive open-source library built on tfhe-rs. We demonstrate the effectiveness of our Blind Counting Sort algorithm by developing a top-k selection algorithm and applying it to privacy-preserving k-Nearest Neighbors classification. This proves to be approximately 4 times faster than state-of-the-art methods.

In spite of being a popular technique for designing block ciphers, Lai-Massey networks have received considerably less attention from a security analysis point of view than Feistel networks and Substitution-Permutation networks. In this paper we study the beyond-birthday-bound (BBB) security of Lai-Massey networks with independent random round functions against chosen-plaintext adversaries. Concretely, we show that five rounds are necessary and sufficient to achieve BBB security.

Fully Homomorphic Encryption (FHE) presents unique challenges in programming due to the contrast between traditional and FHE language paradigms. A key challenge is selecting ciphertext configurations (CCs) to achieve the desired level of security, performance, and accuracy simultaneously. Finding the design point satisfying the goal is often labor-intensive (probably impossible), for which reason previous works settle down to a reasonable CC that brings acceptable performance. When FHE is applied to neural networks (NNs), we have observed that the distinct layered architecture of NN models opens the door for a performance improvement by using layer-wise CCs, because a globally chosen CC may not be the best possible CC for every layer individually. This paper introduces LOHEN, a technique crafted to attain high performance of NN inference by enabling to use layer-wise CC efficiently. Empowered with a cryptographic gadget that allows switching between arbitrary CCs, LOHEN allocates layer-wise CCs for individual layers tailored to their structural properties, while minimizing the increased overhead incurred by CC switching with its capability to replace costly FHE operations. LOHEN can also be engineered to attain higher accuracy, yet deliver higher performance compared to state-of-the-art studies, by additionally adopting the multi-scheme techniques in a layer-wise manner. Moreover, the developers using LOHEN are given the capability of customizing the selection policy to adjust the desired levels of performance and accuracy, subject to their demands. Our evaluation shows that LOHEN improves the NN inference performance in both of these cases when compared to the state-of-the-art. When used to improve the CKKS-only inference, LOHEN improves the NN inference performance of various NNs 1.08--2.88x. LOHEN also improves the performance of mixed-scheme NN inference by 1.34--1.75x without accuracy loss. These two results along with other empirical analyses, advocate that LOHEN can widely help improve the performance of NN inference over FHE.

It is well known that a trusted setup allows one to solve the Byzantine agreement problem in the presence of $t<n/2$ corruptions, bypassing the setup-free $t<n/3$ barrier. Alas, the overwhelming majority of protocols in the literature have the caveat that their security crucially hinges on the security of the cryptography and setup, to the point where if the cryptography is broken, even a single corrupted party can violate the security of the protocol. Thus these protocols provide higher corruption resilience ($n/2$ instead of $n/3$) for the price of increased assumptions. Is this trade-off necessary? We further the study of crypto-agnostic Byzantine agreement among $n$ parties that answers this question in the negative. Specifically, let $t_s$ and $t_i$ denote two parameters such that (1) $2t_i + t_s < n$, and (2) $t_i \leq t_s < n/2$. Crypto-agnostic Byzantine agreement ensures agreement among honest parties if (1) the adversary is computationally bounded and corrupts up to $t_s$ parties, or (2) the adversary is computationally unbounded and corrupts up to $t_i$ parties, and is moreover given all secrets of all parties established during the setup. We propose a compiler that transforms any pair of resilience-optimal Byzantine agreement protocols in the authenticated and information-theoretic setting into one that is crypto-agnostic. Our compiler has several attractive qualities, including using only $O(\lambda n^2)$ bits over the two underlying Byzantine agreement protocols, and preserving round and communication complexity in the authenticated setting. In particular, our results improve the state-of-the-art in bit complexity by at least two factors of $n$ and provide either early stopping (deterministic) or expected constant round complexity (randomized). We therefore provide fallback security for authenticated Byzantine agreement for free for $t_i \leq n/4$.

A Threshold Fully Homomorphic Encryption (ThFHE) scheme enables the generation of a global public key and secret key shares for multiple parties, allowing any threshold of these parties to collaboratively decrypt a ciphertext without revealing their individual secret keys. By leveraging the homomorphic properties of FHE, this scheme supports the distributed computation of arbitrary functions across multiple parties. As distributed execution of cryptographic tasks becomes popular, the demand for ThFHE schemes grows accordingly. We identify three major challenges with existing solutions. (i) They often take unrealistic assumptions with regards to the network model, assuming the threshold of parties to participate in decryption is known a-priori, available throughout multiple communication rounds, and is consistent between parties. (ii) They incur a super-linear overhead on the underlying FHE public parameters. Both issues pose challenges on scaling with the number of parties. (iii) The require heavyweight Zero-Knowledge Proofs (ZKPs) during decryption, thereby introducing a significant computational overhead in order to tolerate malicious behavior. In this work, we introduce a \thfhe scheme that faces the above three challenges simultaneously, and is designed to scale with the number of parties N. Our scheme operates within the well-established asynchronous communication model. At the same time, upon decryption, the ciphertext only incurs a linear 3/4N + t additive overhead on the ciphertext modulus size. Additionally, when allowed to rely on none Post Quantum (PQ)-secure additively homomorphic encryption schemes, we provide a method with an O(1) overhead, independent of N. Lastly, we propose a preprocessing technique, that allows the parties to batch and preprocess all necessary ZKPs in an offline phase, before the encrypted inputs and evaluation circuit are determined. In turn, this enables the system to effectively manage traffic spikes, by exploiting idle periods to preform the ZKPs. We build on a ring-based FHE scheme, specifically using the BGV scheme for clarity and concreteness. Nonetheless, the techniques also apply to BFV, CKKS, and TFHE schemes.

Zero-knowledge proofs (ZKPs) are cryptographic protocols that enable one party to prove the validity of a statement without revealing any information beyond its truth. A central building block in many ZKPs are polynomial commitment schemes (PCS) where constructions with \textit{linear-time provers} are especially attractive. Two such examples are Brakedown and its extension Orion which enable linear-time and quantum-resistant proving by leveraging linear-time encodable Spielman codes. However, these PCS operate over large datasets, creating significant computational bottlenecks. For example, committing to and proving a degree $2^{28}$ polynomial requires around 1.1 GB of data while taking 463 seconds on a high-end server CPU. This work addresses the performance bottleneck in Orion-like PCS by optimizing their most critical operations: Spielman encoding and Merkle commitments. These operations involve Gigabytes of data and suffer from random off-chip memory access patterns that drastically reduce off-chip bandwidth. We resolve this issue and introduce \textit{inverted expander graphs} to eliminate random writes and reduce off-chip memory accesses by over 50\%. Additionally, we propose an on-the-fly graph sampling method that avoids streaming large auxiliary data by generating expander graphs dynamically on-chip. We also provide a formal security proof for our proposed graph transformation. Beyond encoding, we accelerate Merkle Tree construction over large data sets through a scalable multi-pass SHA3 pipeline. Finally, we reutilize existing hardware components used in commitment to accelerate the so-called proximity and consistency checks during proof generation. Building upon these concepts, we present the first hardware architecture for PCS -- with linear prover time -- on a Xilinx Alveo U280 FPGA. In addition, we discuss the practical challenges of manually partitioning, placing, and routing our large-scale architecture to efficiently map it to the multi-SLR and HBM-equipped FPGA. The final implementation achieves a speedup of two orders of magnitude for full proof generation, covering commitment and proving steps. When combined with Virgo as an outer CP-SNARK protocol, our accelerator reduces end-to-end latency by up to 3.85$\times$ --- close to the theoretical maximum of 3.9$\times$.

Plaintext-ciphertext matrix multiplication (PC-MM) is an indispensable tool in privacy-preserving computations such as secure machine learning and encrypted signal processing. While there are many established algorithms for plaintext-plaintext matrix multiplication, efficiently computing plaintext-ciphertext (and ciphertext-ciphertext) matrix multiplication is an active area of research which has received a lot of attention. Recent literature have explored various techniques for privacy-preserving matrix multiplication using fully homomorphic encryption (FHE) schemes with ciphertext packing and Single Instruction Multiple Data (SIMD) processing. On the other hand, there hasn't been any attempt to speed up PC-MM using unpacked additively homomorphic encryption (AHE) schemes beyond the schoolbook method and Strassen's algorithm for matrix multiplication. In this work, we propose an efficient PC-MM from unpacked AHE, which applies Cussen's compression-reconstruction algorithm for plaintext-plaintext matrix multiplication in the encrypted setting. We experimentally validate our proposed technique using a concrete instantiation with the additively homomorphic elliptic curve ElGamal encryption scheme and its software implementation on a Raspberry Pi 5 edge computing platform. Our proposed approach achieves up to an order of magnitude speedup compared to state-of-the-art for large matrices with relatively small element bit-widths. Extensive measurement results demonstrate that our fast PC-MM is an excellent candidate for efficient privacy-preserving computation even in resource-constrained environments.

Know Your Customer (KYC) is a core component of the Anti-Money Laundering (AML) framework, designed to prevent illicit activities within financial systems. However, enforcing KYC and AML on blockchains remains challenging due to difficulties in establishing accountability and preserving user privacy. This study proposes REGKYC, a privacy-preserving Attribute-Based Access Control (ABAC) framework that balances user privacy with externally mandated KYC and AML requirements. REGKYC leverages a structured ABAC model to support the flexible verification of KYC attributes and the enforcement of compliance policies, providing benefits to multiple stakeholders. First, it enables legitimate users to meet compliance requirements while preserving the privacy of their on-chain activities. Second, it empowers Crypto-asset Service Providers (CASPs) to tailor compliance policies to operational needs, ensuring adaptability to evolving regulations. Finally, it enhances regulatory accountability by enabling authorized deanonymization of malicious actors. We hope this work inspires future research to harmonize user privacy and regulatory compliance in blockchain systems.

In this work we formalize the notion of a two-party permutation correlation $(A, B), (C, \pi)$ s.t. $\pi(A)=B+C$ for a random permutation $\pi$ of $n$ elements and vectors $A,B,C\in \mathbb{F}^n$. This correlation can be viewed as an abstraction and generalization of the Chase et al. (Asiacrypt 2020) share translation protocol. We give a systematization of knowledge for how such a permutation correlation can be derandomized to allow the parties to perform a wide range of oblivious permutations of secret-shared data. This systematization immediately enables the translation of various popular honest-majority protocols to be efficiently instantiated in the two-party setting, e.g. collaborative filtering, sorting, database joins, graph algorithms, and many more. We give two novel protocols for efficiently generating a random permutation correlation. The first uses MPC-friendly PRFs to generate a correlation of $n$ elements, each of size $\ell=\log|\mathbb{F}|$ bits, with $O(n\ell)$ bit-OTs, time, communication, and only 3 rounds including setup. Similar asymptotics previously required relatively expensive public-key cryptography, e.g. Paillier or LWE. Our protocol implementation for $n=2^{20},\ell=128$ requires just 7 seconds & $\sim2\ell n$ OTs for communication, a respective 40 & $1.1\times$ improvement on the LWE solution of Juvekar at al. (CCS 2018). The second protocol is based on pseudo-random correlation generators and achieves an overhead that is sublinear in the string length $\ell$, i.e. the communication and number of OTs is $O(n\log \ell)$. The overhead of the latter protocol has larger hidden constants, and therefore is more efficient only when long strings are permuted, e.g. in graph algorithms. Finally, we present a suite of highly efficient protocols based on permutations for performing various batched random access operations. These include the ability to extract a hidden subset of a secret-shared list. More generally, we give ORAM-like protocols for obliviously reading and writing from a list in a batched manner. We argue that this suite of batched random access protocols should be a first class primitive in the MPC practitioner's toolbox.

We examine the post-quantum security of the Ascon authenticated encryption (AE) mode. In spite of comprehensive research of Ascon's classical security, the potential impact of quantum adversaries on Ascon has not yet been explored much. We investigate the generic security of the Ascon AE mode in the setting where the adversary owns a quantum computer to improve its attack, while the adversarial encryption or decryption queries are still classical. In this so-called Q1 model, Ascon achieves security up to approximately $\min\{2^{c/3},2^{k/2}\}$ evaluations, where $c$ is the capacity, $k$ the key size, and the adversary is block-wise adaptive but restricted to one forgery attempt. Our technique is based on applying the semi-classical one-way to hiding (O2H) lemma, and on tailoring the puncture set to the Ascon mode. Additionally, we discuss different parameter choices for Ascon and compare our results to generic quantum attacks, such as Grover-based key search and state recovery.

This work showcases Quatorze-bis, a state-of-the-art Number Theoretic Transform circuit for TFHE-like cryptosystems on FPGAs. It contains a novel modular multiplication design for modular multiplication with a constant for a constant modulus. This modular multiplication design does not require any DSP units or any dedicated multiplier unit, nor does it require extra logic when compared to the state-of-the-art modular multipliers. Furthermore, we present an implementation of a constant multiplier Number Theoretic Transform design for TFHE-like schemes. Lastly, we use this Number Theoretic Transform design to implement a FINAL hardware accelerator for the AMD Alveo U55c which improves the Throughput metric of TFHE-like cryptosystems on FPGAs by a factor 9.28x over Li et al.'s NFP CHES 2024 accelerator and by 10-25% over the absolute state-of-the-art design FPT while using one third of FPTs DSPs.

We revisit the longstanding open problem of implementing Nakamoto's proof-of-work (PoW) consensus based on a real-world computational task $T(x)$ (as opposed to artificial random hashing), in a truly permissionless setting where the miner itself chooses the input $x$. The challenge in designing such a Proof-of-Useful-Work (PoUW) protocol, is using the native computation of $T(x)$ to produce a PoW certificate with prescribed hardness and with negligible computational overhead over the worst-case complexity of $T(\cdot)$ -- This ensures malicious miners cannot ``game the system" by fooling the verifier to accept with higher probability compared to honest miners (while using similar computational resources). Indeed, obtaining a PoUW with $O(1)$-factor overhead is trivial for any task $T$, but also useless. Our main result is a PoUW for the task of Matrix Multiplication $\mathsf{MatMul}(A,B)$ of arbitrary matrices with $1+o(1)$ multiplicative overhead compared to na\"ive $\mathsf{MatMul}$ (even in the presence of Fast Matrix Multiplication-style algorithms, which are currently impractical). We conjecture that our protocol has optimal security in the sense that a malicious prover cannot obtain any significant advantage over an honest prover. This conjecture is based on reducing hardness of our protocol to the task of solving a batch of low-rank random linear equations which is of independent interest. Since $\mathsf{MatMul}$s are the bottleneck of AI compute as well as countless industry-scale applications, this primitive suggests a concrete design of a new L1 base-layer protocol, which nearly eliminates the energy-waste of Bitcoin mining -- allowing GPU consumers to reduce their AI training and inference costs by ``re-using" it for blockchain consensus, in exchange for block rewards (2-for-1). This blockchain is currently under construction.

An anonymous credential (AC) system with partial disclosure allows users to prove possession of a credential issued by an issuer while selectively disclosing a subset of their attributes to a verifier in a privacy-preserving manner. In keyed-verification AC (KVAC) systems, the issuer and verifier share a secret key. Existing KVAC schemes rely on computationally expensive zero-knowledge proofs during credential presentation, with the presentation size growing linearly with the number of attributes. In this work, we propose two highly efficient KVAC constructions that eliminate the need for zero-knowledge proofs during the credential presentation and achieve constant-size presentations. Our first construction adapts the approach of Fuchsbauer et al. (JoC'19), which achieved constant-size credential presentation in a publicly verifiable setting using their proposed structure-preserving signatures on equivalence classes (SPS-EQ) and set commitment schemes, to the KVAC setting. We introduce structure-preserving message authentication codes on equivalence classes (SP-MAC-EQ) and designated-verifier set commitments (DVSC), resulting in a KVAC system with constant-size credentials (2 group elements) and presentations (5 group elements). To avoid the bilinear groups and pairing operations required by SP-MAC-EQ, our second construction uses a homomorphic MAC with a simplified DVSC. While this sacrifices constant-size credentials ($n+2$ group elements, where $n$ is the number of attributes), it retains constant-size presentations (2 group elements) in a pairingless setting. We formally prove the security of both constructions and provide open-source implementation results demonstrating their practicality. We extensively benchmarked our KVAC protocols and, additionally, bechmarked the efficiency of our SP-MAC-EQ scheme against the original SPS-EQ scheme, showcasing significant performance improvements.

Generalized secret sharing (GSS) enables flexible access control in distributed systems by allowing secrets to be shared across arbitrary monotone access structures. However, its adoption in transparent and trustless environments is hindered due to the reliance on trusted participants and secure communication channels. This reliance restricts GSS's ability to provide flexible control in the presence of adversaries. In this paper, we propose publicly verifiable generalized secret sharing (PVGSS), a scheme that allows to distribute a secret using generalized access structures while enabling non-interactive public verifiability of participant honesty. PVGSS scheme offers significant potential to advance the fields of blockchain and applied cryptography, such as attribute-based cryptosystem, fine-grained MPC and on-chain secret escrow. Intuitively, we first build two GSS schemes by leveraging recursive Shamir secret sharing and linear secret sharing scheme. Then, we encrypt GSS shares and generate the corresponding non-interactive zero-knowledge proofs. Further, we innovatively adopt the GSS reconstruction algorithm to prove that all the encrypted shares are bound to the dealer's secret with only $O(n)$ verification complexity. To exemplify the practical applicability, we implement a decentralized exchange (DEX) protocol, where fairness and accountable arbitration are considered. Our benchmarks on the BN128 curve demonstrate the computational efficiency of PVGSS schemes, while Ethereum gas cost analysis confirms the viability of the DEX implementation.

Bitcoin is the most secure blockchain in the world, supported by the immense hash power of its Proof-of-Work miners. Proof-of-Stake chains are energy-efficient, have fast finality but face several security issues: susceptibility to non-slashable long-range safety attacks, low liveness resilience and difficulty to bootstrap from low token valuation. We show that these security issues are inherent in any PoS chain without an external trusted source, and propose a new protocol, Babylon, where an off-the-shelf PoS protocol checkpoints onto Bitcoin to resolve these issues. An impossibility result justifies the optimality of Babylon. A use case of Babylon is to reduce the stake withdrawal delay: our experimental results show that this delay can be reduced from weeks in existing PoS chains to less than 5 hours using Babylon, at a transaction cost of less than 10K USD per annum for posting the checkpoints onto Bitcoin.

We consider constructions that combine outputs of a single permutation $\pi:\{0,1\}^n \rightarrow \{0,1\}^n$ using a public function. These are popular constructions for achieving security beyond the birthday bound when implementing a pseudorandom function using a block cipher (i.e., a pseudorandom permutation). One of the best-known constructions (denoted SXoP$[2,n]$) XORs the outputs of 2 domain-separated calls to $\pi$. Modeling $\pi$ as a uniformly chosen permutation, several previous works proved a tight information-theoretic indistinguishability bound for SXoP$[2,n]$ of about $q/2^{n}$, where $q$ is the number of queries. However, tight bounds are unknown for the generalized variant (denoted SXoP$[r,n]$) which XORs the outputs of $r \geq 2$ domain-separated calls to a uniform permutation. In this paper, we obtain two results. Our first result improves the known bounds for SXoP$[r,n]$ for all (constant) $r \geq 3$ (assuming $q \leq O(2^n/r)$ is not too large) in both the single-user and multi-user settings. In particular, for $r=3$, our bound is about $\sqrt{u}q_{\max}/2^{2.5n}$ (where $u$ is the number of users and $q_{\max}$ is the maximal number of queries per user), improving the best-known previous result by a factor of at least $2^n$. For odd $r$, our bounds are tight for $q > 2^{n/2}$, as they match known attacks. For even $r$, we prove that our single-user bounds are tight by providing matching attacks. Our second and main result is divided into two parts. First, we devise a family of constructions that output $n$ bits by efficiently combining outputs of 2 calls to a permutation on $\{0,1\}^n$, and achieve multi-user security of about $\sqrt{u} q_{\max}/2^{1.5n}$. Then, inspired by the CENC construction of Iwata [FSE'06], we further extend this family to output $2n$ bits by efficiently combining outputs of 3 calls to a permutation on $\{0,1\}^n$. The extended construction has similar multi-user security of $\sqrt{u} q_{\max}/2^{1.5n}$. The new single-user ($u=1$) bounds of $q/2^{1.5n}$ for both families should be contrasted with the previously best-known bounds of $q/2^n$, obtained by the comparable constructions of SXoP$[2,n]$ and CENC. All of our bounds are proved by Fourier analysis, extending the provable security toolkit in this domain in multiple ways.

Sampling a non degenerate (that is, invertible) square matrix over a finite field is easy, draw a random square matrix and discard if the determinant is zero. We address the problem in higher dimensions, and sample non degenerate boundary format tensors, which generalise square matrices. Testing degeneracy is conjectured to be hard in more than two dimensions, precluding the "draw a random tensor and discard if degenerate'' recipe. The difficulty is in computing hyperdeterminants, higher dimensional analogues of determinants. Instead, we start with a structured random non degenerate tensor and scramble it by infusing more randomness while still preserving non degeneracy. We propose two kinds of scrambling. The first is multiplication in each dimension by random invertible matrices, which preserves dimension and format. Assuming pseudo randomness of this action, which also underlies tensor isomorphism based cryptography, our samples are computationally indistinguishable from uniform non degenerate tensors. The second scrambling employs tensor convolution (that generalises multiplication by matrices) and can increase dimension. Inspired by hyperdeterminant multiplicativity, we devise a recursive sampler that uses tensor convolution to reduce the problem from arbitrary to three dimensions. Our sampling is a candidate solution for drawing public keys in tensor isomorphism based cryptography, since non degenerate tensors elude recent weak key attacks targeting public key tensors either containing geometric structures such as "triangles" or being deficient in tensor rank. To accommodate our sampling, tensor isomorphism based schemes need to be instantiated in boundary formats such as (2k+1) x (k+1) x (k+1), away from the more familiar k x k x k cubic formats. Our sampling (along with the recent tensor trapdoor one-way functions) makes an enticing case to transition tensor isomorphism cryptography to boundary formats tensors, which are true analogues of square matrices.

Some of our current public key methods use a trap door to implement digital signature methods. This includes the RSA method, which uses Fermat's little theorem to support the creation and verification of a digital signature. The problem with a back-door is that the actual trap-door method could, in the end, be discovered. With the rise of PQC (Post Quantum Cryptography), we will see a range of methods that will not use trap doors and provide stronger proof of security. In this case, we use hash-based signatures (as used with SPHINCS+) and Fiat Shamir signatures using Zero Knowledge Proofs (as used with Dilithium).

As billions of people rely on end-to-end encrypted messaging, the exposure of metadata, such as communication timing and participant relationships, continues to deanonymize users. Asynchronous metadata-hiding solutions with strong cryptographic guarantees have historically been bottlenecked by quadratic $O(N^2)$ server computation in the number of users $N$ due to reliance on private information retrieval (PIR). We present Myco, a metadata-private messaging system that preserves strong cryptographic guarantees while achieving $O(N \log^2 N)$ efficiency. To achieve this, we depart from PIR and instead introduce an oblivious data structure through which senders and receivers privately communicate. To unlink reads and writes, we instantiate Myco in an asymmetric two-server distributed-trust model where clients write messages to one server tasked with obliviously transmitting these messages to another server, from which clients read. Myco achieves throughput improvements of up to 302x over multi-server and 2,219x over single-server state-of-the-art systems based on PIR.

This paper examines how quantum computing enhances the encryption system. It studies the relationship between cryptography and quantum physics. The paper considers the historical progression of encryption techniques paying attention to the altering nature of security challenges. Moreover, it analyzes the basic principles of quantum computing, describing its theoretical concept and its advantages over classical systems in terms of potential performance. Also, it focuses on an in-depth analysis of Grovers’ Algorithm showing its unique searching capability and its implications for encryption schemes. The paper also reviews the limitations of Grover’s Algorithm that could make it vulnerable to attacks and how to make it safer. Also, the methods of quantum computing that create strong encryption are briefly outlined. Overall, in the quest for secure systems of communication in the era of quantum, the paper aims at the futuristic paradigm shift by considering the emergence of Quantum-Powered Encryption Systems. It answers key questions about this subject through both, qualitative and quantitative analysis. The provided scientific report supplements the existing body of knowledge about the relationship between quantum computers and encryption systems and sets the foundation for better and more secure encryption for the digital world.

The security of the Elliptic Curve Digital Signature Algorithm (ECDSA) depends on the uniqueness and secrecy of the nonce, which is used in each signature. While it is well understood that nonce $k$ reuse across two distinct messages can leak the private key, we show that even if a distinct value is used for $k_2$, where an affine relationship exists in the form of: \(k_m = a \cdot k_n + b\), we can also recover the private key. Our method requires only two signatures (even over the same message) and relies purely on algebra, with no need for lattice reduction or brute-force search(if the relationship, or offset, is known). To our knowledge, this is the first closed-form derivation of the ECDSA private key from only two signatures over the same message, under a known affine relationship between nonces.

Abstract. CHVote is one of the two main electronic voting systems developed in the context of political elections in Switzerland, where the regulation requires a specific setting and specific trust assumptions. We show that actually, CHVote fails to achieve vote secrecy and individual verifiability (here, recorded-as-intended), as soon as one of the online components is dishonest, contradicting the security claims of CHVote. In total, we found 9 attacks or variants against CHVote, 2 of them being based on a bug in the reference implementation. We confirmed our findings through a proof-of-concept implementation of our attacks.

The CKKS Fully Homomorphic Encryption (FHE) scheme enables approximate arithmetic on encrypted complex numbers for a desired precision. Most implementations use RNS with carefully chosen parameters to balance precision, efficiency, and security. However, a key limitation in RNS-CKKS is the rigid coupling between the scale factor, which determines numerical precision, and the modulus, which ensures security. Since these parameters serve distinct roles—one governing arithmetic correctness and the other defining cryptographic structure—this dependency imposes design constraints, such as a lack of suitable NTT primes and limited precision flexibility, ultimately leading to inefficiencies. We propose Grafting, a novel approach to decouple scale factors from the modulus by introducing (universal) sprouts, reusable modulus factors that optimize word-sized packing while allowing flexible rescaling. With the universal property, sprouts allow rescaling by arbitrary bit-lengths and key-switching at any modulus bit-length without requiring additional key-switching keys. Decoupling the scale factor from the modulus in Grafting yields significant efficiency gains: (1) Optimized RNS packing by decomposing the modulus into machine word-sized components, accelerating computations and reducing the ciphertext and encryption/evaluation key sizes; and (2) A freely adjustable scale factor independent of the modulus, unifying the ring structure across applications and reducing modulus consumption through adaptive scalings. Our experiments demonstrate that Grafting improves performance across standard SHE/FHE parameter sets for ring dimensions $2^{14}$-$2^{16}$ by up to $1.83\times$ and $2.01\times$ for key-switchings and multiplications, respectively, and up to $1.92\times$ for bootstrapping. Grafting also reduces public key and ciphertext sizes by up to $62\%$ without compressions, maintaining the same number of public keys as before. As an application, we showcase the CKKS gate bootstrapping for bits (Bae et al.; Eurocrypt'24), achieving $1.89\times$ speed-up due to the reduced number of RNS factors. Finally, we revisit the homomorphic comparison (Cheon et al.; Asiacrypt'20), evaluating it with carefully chosen scale factors for each iteration, reporting up to $204$-bit fewer modulus consumption ($27\%$ reduction) in the standard parameter set, without precision loss.

Proxy re-encryption (PRE) schemes allow a delegator to designate a proxy to re-encrypt its ciphertext into a ciphertext that the delegatee can decrypt. In contrast, the proxy gains nothing helpful from this transformation. This decryption-power transfer is proper in applications of encrypted email forwarding, key escrow, and publish/subscribe systems. The security notions for PRE are inherited from the standard public key encryption (PKE) schemes, i.e., indistinguishability under chosen-plaintext attacks (CPA) and security under chosen-ciphertext attacks (CCA). A recently popular notion, indistinguishability under honest re-encryption attacks (HRA), was proposed by Cohen in 2019, indicating that CPA security is insufficient for PRE because some CPA-secure PRE leaks the secret key of the delegator. Many post-quantum secure PRE schemes have recently been designed under the HRA security model. However, HRA security differs from traditional CCA security, and there is no known reduction between them. The existing results show they appear to be incompatible. This paper aims to bridge those two security notions via reductions. In addition, we found that many existing HRA-secure schemes are vulnerable to collusion. We provide a generic transformation from a CPA-secure PRE to a collusion-resistant and CPA-secure PRE. This transformation also applies to HRA-secure PREs.

Federated Learning (FL) allows clients to engage in learning without revealing their raw data. However, traditional FL focuses on developing a single global model for all clients, limiting their ability to have personalized models tailored to their specific needs. Personalized FL (PFL) enables clients to obtain their customized models, either with or without a central party. Current PFL research includes mechanisms to detect poisoning attacks, in which a couple of malicious nodes try to manipulate training convergence by submitting misleading data. However, these detection approaches often overlook privacy concerns, as they require clients to share their models with all other clients. This paper extends BALANCE, a personalized poisoning detection mechanism based on client models and their expectations. Our method enhances both security and privacy by ensuring clients are not required to share their model data with other clients. By leveraging server-assisted PFL and Fully Homomorphic Encryption (FHE), we enable a central party to identify unpoisoned clients from the perspective of individual clients and train personalized models securely. Additionally, we introduce an efficient personalized client selection algorithm that prevents redundant checks and ensures the inheritance of unpoisoned clients.

We present concrete techniques for adapting the protocols of Mohassel et al (CCS 2020) and Badrinarayanan et al (CCS 2022) for compute SQL-like querying operations on secret shared database tables to the two party setting. The afore mentioned protocols are presented in a generic setting with access to certain idealized functionalities, e.g. secret shared permutations. However, they only instantiate their protocols in the honest majority three party setting due to other settings being considered too inefficient. We show that this is no longer the case. In particular, the recent work of Peceny et al. (eprint 2024) gives a concretely efficient two party permutation protocol. Additionally, we give a new and highly efficient protocol for evaluating the strong PRF recently proposed by Alamati et al. (Crypto 2024). Building on these advancements, along with a variety of protocol improvements and significant cryptographic engineering, our open source implementation demonstrate concretely efficient two party SQL-like querying functionality on secret shared data. We focus on the two party setting with secret shared input and output tables. The first protocol $\Pi_\textsf{Join-OO}$ is designed for the setting where the join keys are unique, similar to Private Set Intersection (PSI) except that the inputs and output are secret shared. This protocol is constant round and $O(n)$ running time. The secret protocol $\Pi_\textsf{Join-OM}$ allows one of the tables to contain repeating join keys. Our instantiations achieves $O(n\log n)$ running time and $O(\log n)$ rounds of interaction.

Searchable encryption (SE) enables privacy-preserving keyword search on encrypted data. Public-key SE (PKSE) supports multi-user searches but suffers from high search latency due to expensive public-key operations. Symmetric SE (SSE) offers a sublinear search but is mainly limited to single-user settings. Recently, hybrid SE (HSE) has combined SSE and PKSE to achieve the best of both worlds, including multi-writer encrypted search functionalities, forward privacy, and sublinear search with respect to database size. Despite its advantages, HSE inherits critical security limitations, such as susceptibility to dictionary attacks, and still incurs significant overhead for search access control verification, requiring costly public-key operation invocations (i.e., pairing) across all authorized keywords. Additionally, its search access control component must be rebuilt periodically for forward privacy, imposing substantial writer overhead. In this paper, we propose Hermes, a new HSE scheme that addresses the aforementioned security issues in prior HSE designs while maintaining minimal search complexity and user efficiency at the same time. Hermes enables multi-writer encrypted search functionalities and offers forward privacy along with resilience to dictionary attacks. To achieve this, we develop a new identity-based encryption scheme with hidden identity and key-aggregate properties, which could be of independent interest. We also design novel partitioning and epoch encoding techniques in Hermes to minimize search complexity and offer low user overhead in maintaining forward privacy. We conducted intensive experiments to assess and compare the performance of Hermes and its counterpart on commodity hardware. Experimental results showed that Hermes performs search one to two orders of magnitude faster than the state-of-the-art HSE while offering stronger security guarantees to prevent dictionary and injection attacks.

In pairing-based cryptography, the final exponentiation with a large fixed exponent is crucial for ensuring unique outputs in both Tate and optimal ate pairings. While significant strides have been made in optimizing elliptic curves with even embedding degrees, progress remains limited for curves with odd embedding degrees, especially those divisible by $3$. This paper introduces novel techniques to optimize the computation of the final exponentiation for the optimal ate pairing on such curves. The first technique leverages the structure of certain existing seeds to enable the use of cyclotomic cubing and extends this concept to generate new seeds with similar characteristics. The second technique focuses on producing new sparse ternary representation seeds to utilize cyclotomic cubing as a replacement for squaring. These approaches result in performance improvements of up to $19.3\%$ in the computation of the final exponentiation for the optimal ate pairing on $BLS15$ and $BLS27$ curves.

The major Fully Homomorphic Encryption (FHE) schemes guarantee the privacy of the encrypted message only in the honest-but-curious setting, when the server follows the protocol without deviating. However, various attacks in the literature show that an actively malicious server can recover sensitive information by executing incorrect functions, tampering with ciphertexts, or observing the client’s reaction during decryption. Existing integrity solutions for FHE schemes either fail to guarantee circuit privacy, exposing the server's computations to the client, or introduce significant computational overhead on the prover by requiring proofs of FHE operations on ciphertexts. In this work, we present Fherret, a novel scheme leveraging the MPC-in-the-Head (MPCitH) paradigm to provide a proof of correct-and-honest homomorphic evaluation while preserving circuit privacy. This proof guarantees that the client can safely decrypt the ciphertext obtained from the server without being susceptible to reaction-based attacks, such as verification and decryption oracle attacks. Additionally, this proof guarantees that the server’s evaluation maintains correctness, thereby protecting the client from $\mathsf{IND}\text{-}\mathsf{CPA}^{\mathsf{D}}$-style attacks. Our solution achieves a prover overhead of $4\lambda$ homomorphic evaluations of random functions from the function space $\mathcal{F}$, while retaining a competitive verifier overhead of $2 \lambda$ homomorphic evaluations and a communication size proportional to $\sqrt{2\lambda}$ times the size of a function from $\mathcal{F}$. Furthermore, Fherret is inherently parallelizable, achieving a parallel computation overhead similar to a homomorphic evaluation of a random function from $\mathcal{F}$ for both the prover and the verifier.

We show that here standard decoding algorithms for generic linear codes over a finite field can speeded up by a factor which is essentially the size of the finite field by reducing it to a low weight codeword problem and working in the relevant projective space. We apply this technique to SDitH and demonstrate that the parameters of the original submission fail to meet the security requirements set by NIST. However, the updated version, released after the discovery of this attack, is no longer challenged by our attack.

This document is a preliminary version of what is intended to be submitted to NIST by Zama as part of their threshold call. The document also serves as partial documentation of the protocols used in the Zama MPC system for threshold TFHE. However, note that the Zama software includes many optimizations built on top of the simple specifications given here. In particular the TFHE parameters given here are larger than those used by the Zama software. This is because the Zama TFHE library contains optimizations which are beyond the scope of this document. Thus the parameters given in this document are compatible with the description of TFHE given here, and take no account of the extra optimizations in the Zama software. Also note that we describe more protocols than that provided in the Zama software. In particular this document describes BGV and BFV threshold implementations, MPC-in-the-Head based proofs of correct encryption. We present mechanisms to perform robust threshold key generation and decryption for Fully Homomorphic Encryption schemes such as BGV, BFV and TFHE, in the case of super honest majority, t < n/3, or t < n/4, in the presence of malicious adversaries. The main mechanism for threshold decryptions follow the noise flooding principle, which we argue is sufficient for BGV and BFV. For TFHE a more subtle technique is needed to apply noise flooding, since TFHE parameters are small. To deal with all three FHE scheme, and obtain a unified framework for all such schemes, we are led to consider secret sharing over Galois Rings and not just finite fields. We consider two sets of threshold profiles, depending on whether binomial(n,t) is big or small. In the small case we obtain for all schemes an asynchronous protocol for robust threshold decryption, and we obtain a robust synchronous protocol for threshold key generation; both with t < n/3. For the large case we only support TFHE, and our protocols require an “offline phase” which requires synchronous networks and can “only” tolerate t < n/4. The threshold key generation operation, and the above mentioned offline phase, require access to a generic offline MPC functionality over arbitrary Galois Rings. This functionality is fully specified here. Finally, we present Zero-Knowledge proof techniques for proving the valid encryption of an FHE ciphertext. These proofs are important in a number of application contexts.

Deep learning-based side-channel analysis is an extremely powerful option for profiling side-channel attacks. However, to perform well, one needs to select the neural network model and training time hyperparameters carefully. While many works investigated these aspects, random search could still be considered the current state-of-the-art. Unfortunately, random search has drawbacks, since the chances of finding a good architecture significantly drop when considering more complex targets. In this paper, we propose a novel neural architecture search approach for SCA based on grammatical evolution - SCAGE. We define a custom SCA grammar that allows us to find well-performing and potentially unconventional architectures. We conduct experiments on four datasets, considering both synchronized and desynchronized versions, as well as using feature intervals or raw traces. Our results show SCAGE to perform extremely well in all settings, outperforming random search and related works in most of the considered scenarios.

Password Authenticated Key Exchange (PAKE) establishes secure communication channels using relatively short, often human memorable, passwords for authentication. The currently standardized PAKEs however rely on classical asymmetric (public key) cryptography. Thus, these classical PAKEs may become insecure, should the expected quantum threat become a reality. Despite the growing interest in realizing quantum-safe PAKEs, they did not receive much attention from the ongoing Post-Quantum Cryptography (PQC) integration efforts. Thus, there is a significant gap in awareness compared to PQC primitives subject to the official governmental and institutional standardization processes. In this work, we provide a comprehensive overview of the existing PQC PAKEs focusing on their design rationales, authentication methods and asymmetric key agreement primitives. Further, we classify PQC PAKEs w.r.t. their properties and security assurances. Finally, we address PAKE designs that are still unexplored in the PQC realm and discuss the possibility of their adaptation. Thus, we offer a detailed reference for future work on PQC PAKEs.

At CRYPTO 2019, Gohr pioneered the integration of differential cryptanalysis with neural networks, demonstrating significant advantages over traditional distinguishers. Subsequently, at Inscrypt 2020, Su et al. proposed the concept of constructing polyhedral differential neural distinguishers by leveraging multiple effective input differences. More recently, at FSE 2024, Bellini et al. introduced a general-purpose tool for automating the training of single-key differential neural distinguishers for various block ciphers. Inspired by this body of work, we aim to extend automated search techniques to related-key differential neural distinguishers, enabling the discovery of effective input differences and key differences for such distinguishers. To achieve this, we employ a genetic optimization algorithm to identify effective differential combinations. To validate the efficacy of our method, we apply it to the Simeck and Simon cipher families, successfully identifying effective differential combinations for the three variants of Simeck and ten variants of Simon. Furthermore, inspired by the concept of polyhedral neural distinguishers, we adopt a novel data format that leverages multiple distinct input differences and key differences to construct positive and negative samples, providing the neural network with a richer set of features. Our approach not only identify high-quality distinguishers for previously unexplored cipher variants but also achieve higher accuracy for related-key differential neural distinguishers compared to the state-of-the-art.

Amortized bootstrapping techniques have been proposed for FHEW/TFHE to efficiently refresh multiple ciphertexts simultaneously within a polynomial modulus. Although recent proposals have very efficient asymptotic complexity, reducing the amortized cost essentially to $\tilde{O}(1)$ FHE multiplications, the practicality of such algorithms still suffers from substantial overhead and high decryption failure rates (DFR). In this study, we improve upon one of the state-of-the-art amortized bootstrapping algorithms (Guimarães et al., ASIACRYPT 2023) for FHEW/TFHE-like schemes by introducing an alternative algorithmic strategy. Specifically, we combine Guimarães et al.'s strategy based on a two-part NTT with an incomplete Number Theoretic Transform (NTT) algorithm. As a result, we demonstrate a 2.12$\times$ speedup compared to the algorithm of Guimarães et al. and a $1.12\times$ improvement over the state-of-the-art (sequential) TFHE-rs while achieving a DFR close to $2^{-32}$ for 7-bit messages, although the DFR is higher for 8-bit messages. We also explore trade-offs between execution time and DFR, identifying parameter sets that improve execution time of Guimarães et al. by $1.41\times$, while simultaneously reducing the DFR by a factor of $2^{-22}$ for 8-bit messages.

Much work has been done recently on developing password-authenticated key exchange (PAKE) mechanisms with post-quantum security. However, modern guidance recommends the use of hybrid schemes—schemes which rely on the combined hardness of a post-quantum assumption, e.g., Learning with Errors (LWE), and a more traditional assumption, e.g., decisional Diffie-Hellman. To date, there is no known hybrid PAKE construction, let alone a general method for achieving such. In this paper, we present two efficient PAKE combiners—algorithms that take two PAKEs satisfying mild assumptions, and output a third PAKE with combined security properties—and prove these combiners secure in the Universal Composability (UC) model. Our sequential combiner, instantiated with efficient existing PAKEs such as CPace (built on Diffie-Hellman-type assumptions) and CAKE (built on lattice assumptions), yields the first known hybrid PAKE.

Federated Learning (FL) enables multiple clients to collaboratively train a machine learning model while keeping their data private, eliminating the need for data sharing. Two common approaches to secure aggregation (SA) in FL are the single-aggregator and multiple-aggregator models. This work focuses on improving the multiple-aggregator model. Existing multiple-aggregator protocols such as Prio (NSDI 2017), Prio+ (SCN 2022), Elsa (S&P 2023) either offer robustness only in the presence of semi-honest servers or provide security without robustness and are limited to two aggregators. We introduce Mario, the first multiple-aggregator Secure Aggregation protocol that is both secure and robust in a malicious setting. Similar to prior work of Prio and Prio+, Mario provides secure aggregation in a setup of $n$ servers and $m$ clients. Unlike previous work, Mario removes the assumption of semi-honest servers, and provides a complete protocol with robustness under malicious clients and malicious servers. Our implementation shows that \system is $3.40\times$ and $283.4\times$ faster than Elsa and Prio+, respecitively.

Web3 applications, such as on-chain games, NFT minting, and leader elections necessitate access to unbiased, unpredictable, and publicly verifiable randomness. Despite its broad use cases and huge demand, there is a notable absence of comprehensive treatments of on-chain verifiable randomness services. To bridge this, we offer an extensive formal analysis of on-chain verifiable randomness services. We present the $first$ formalization of on-chain verifiable randomness in the blockchain setting by introducing the notion of Verifiable Randomness as a Service (VRaaS). We formally define VRaaS using an ideal functionality $\mathcal{F}_{\text{VRaaS}}$ in the Universal Composability model. Our definition not only captures the core features of randomness services, such as unbiasability, unpredictability, and public verifiability, but also accounts for many other crucial nuances pertaining to different entities involved, such as smart contracts. Within our framework we study a generic design of Verifiable Random Function (VRF)-based randomness service - where the randomness requester provides an input on which the randomness is evaluated as VRF output. We show that it does satisfy our formal VRaaS definition. Furthermore, we show that the generic protocol captures many real-world randomness services like Chainlink VRF and Supra dVRF. Moreover, we investigate the minimalism of the framework. Towards that, first we show that, the two transactions in-built in our framework are actually $necessary$ for any randomness service to support the essential qualities. We also discover $practical$ $vulnerabilities$ in other designs such as Algorand beacon, Pyth VRF and Band VRF, captured within our framework.

PLONK is a prominent universal and updatable zk-SNARK for general circuit satisfiability, which allows a prover to produce a short certificate of the validity of a certain statement/computation. Its expressive model of computation and its highly efficient verifier complexity make PLONK a powerful tool for a wide range of blockchain applications. Supporting standard cryptographic primitives (such us ECDSA over SECP256k1) or advanced recursive predicates (e.g. incrementally verifiable computation) on a SNARK presents a significant challenge. It requires so-called foreign-field arithmetic (enforcing constraints over algebraic fields that differ from the SNARK native field) which was previously believed to incur an overhead of two or three orders of magnitude. We build on the techniques by Lubarov and Baylina and observe that, by considering tight bounds on their encoding of foreign-field multiplication, the number of PLONK constraints can be significantly reduced. We show that these techniques also extend to elliptic curve emulation, with an overhead of just one order of magnitude (with respect to its native counterpart). We validate soundness and completeness of our main results in EasyCrypt. Finally, we implement an open-source library with support for foreign-field arithmetic. Our experimental results showcase the generality of our techniques and confirm their suitability for real-world applications.

In an anonymous credential system, users collect credentials from issuers, and can use their credentials to generate privacy-preserving identity proofs that can be shown to third-party verifiers. Since the introduction of anonymous credentials by Chaum in 1985, there has been promising advances with respect to system design, security analysis and real-world implementations of anonymous credential systems. In this paper, we examine Hyperledger AnonCreds, an anonymous credential system that was introduced in 2017 and is currently undergoing specification. Despite being implemented in deployment-ready identity system platforms, there is no formal security analysis of the Hyperledger AnonCreds protocol. We rectify this, presenting syntax and a security model for, and a first security analysis of, the Hyperledger AnonCreds protocol. In particular, we demonstrate that Hyperledger AnonCreds is correct, and satisfies notions of unforgeability and anonymity. We conclude with a discussion on the implications of our findings, highlighting the importance of rigorous specification efforts to support security evaluation of real-world cryptographic protocols.

A long-standing question in the blockchain community is which class of computations are efficiently expressible in cryptocurrencies with limited scripting languages, such as Bitcoin Script. Such languages expose a reduced trusted computing base, thereby being less prone to hacks and vulnerabilities, but have long been believed to support only limited classes of payments. In this work, we confute this long-standing belief by showing for the first time that arbitrary computations can be encoded in today's Bitcoin Script without introducing any language modification or additional security assumptions, such as trusted hardware, trusted parties, or committees with an honest majority. We present BitVM, a two-party protocol that realizes a generic virtual machine by combining cryptographic primitives and economic incentives. We conduct a formal analysis of BitVM, characterizing its functionality, system assumptions, and security properties. We further demonstrate the practicality of our approach by implementing a prototype and performing an experimental evaluation: in the optimistic case (i.e., when parties agree), our protocol requires just three on-chain transactions, whereas in the pessimistic case, the number of transactions grows logarithmically with the size of the virtual machine. We exemplify the deployment potential of BitVM by building a Bitcoin-sidechain bridge application. This work not only solves a long-standing theoretical problem, but it also promises a strong practical impact, enabling the development of complex applications in Bitcoin.

Safety and liveness are the two classical security properties of consensus protocols. Recent works have strengthened safety with accountability: should any safety violation occur, a sizable fraction of adversary nodes can be proven to be protocol violators. This paper studies to what extent analogous accountability guarantees are achievable for liveness. To reveal the full complexity of this question, we introduce an interpolation between the classical synchronous and partially-synchronous models that we call the $x$-partially-synchronous network model in which, intuitively, at most an $x$ fraction of the time steps in any sufficiently long interval are asynchronous (and, as with a partially-synchronous network, all time steps are synchronous following the passage of an unknown "global stablization time"). We prove a precise characterization of the parameter regime in which accountable liveness is achievable: if and only if $x < 1/2$ and $f < n/2$, where $n$ denotes the number of nodes and $f$ the number of nodes controlled by an adversary. We further refine the problem statement and our analysis by parameterizing by the number of violating nodes identified following a liveness violation, and provide evidence that the guarantees achieved by our protocol are near-optimal (as a function of $x$ and $f$). Our results provide rigorous foundations for liveness-accountability heuristics such as the "inactivity leaks" employed in Ethereum.

Most homomorphic encryption (FHE) schemes exploit a technique called single-instruction multiple-data (SIMD) to process several messages in parallel. However, they base their security in somehow strong assumptions, such as the hardness of approximate lattice problems with superpolynomial approximation factor. On the other extreme of the spectrum, there are lightweight FHE schemes that have much faster bootstrapping but no SIMD capabilities. On the positive side, the security of these schemes is based on lattice problems with (low-degree) polynomial approximation factor only, which is a much weaker security assumption. Aiming the best of those two options, Micciancio and Sorrell (ICALP'18) proposed a new amortized bootstrapping that can process many messages at once, yielding sublinear time complexity per message, and allowing one to construct FHE based on lattice problems with polynomial approximation factor. Some subsequent works on this line achieve near-optimal asymptotic performance, nevertheless, concrete efficiency remains mostly an open problem. The only existing implementation to date (GPV23, Asiacrypt 2023) requires keys of up to a hundred gigabytes while only providing gains for relatively large messages. In this paper, we introduce a new method for amortized bootstrapping where the number of homomorphic operations required per message is $O(h)$ and the noise overhead is $O(\sqrt{h \lambda} \log \lambda)$, where $h$ is the Hamming weight of the LWE secret key and $\lambda$ is the security parameter. This allows us to use much smaller parameters and to obtain faster running time. Our method is based on a new efficient homomorphic evaluation of sparse polynomial multiplication. We bootstrap 2 to 8-bit messages in 1.1 ms to 26.5 ms, respectively. Compared to TFHE-rs, this represents a performance improvement of 3.9 to 41.5 times while requiring bootstrapping keys up to 50.4 times smaller.

This paper compares the relative strengths of prominent security notions for onion encryption within the Tor setting, specifically focusing on CircuitHiding (EUROCRYPT 2018, an anonymity flavor notion) and OnionAE (PETS 2018, a stateful authenticated encryption flavor notion). Although both are state-of-the-art, Tor-specific notions, they have exhibited different definitional choices, along with variations in complexity and usability. By employing an indirect approach, we compare them using a set of onion layer-centric notions: IND\$-CPA, IPR/IPR$^+$, and INT-sfCTXT, to compare with the two, respectively. Since the same notion set that implies OnionAE does not imply CircuitHiding, and vice versa, this leads to the conclusion that OnionAE and CircuitHiding are mutually separable. Therefore, neither notion fully expresses satisfactory security on its own. Importantly, IND\$-CPA, IPR$^+$ (a stronger variant of IPR), and INT-sfCTXT collectively and strictly imply OnionAE and CircuitHiding. Given their onion layer-centric and thus simpler nature, this provides a practical approach to simultaneously satisfying CircuitHiding and OnionAE. While the formal treatment of (general) public-key onion routing has been relatively well-studied, formal treatment tailored to Tor remains insufficient, and thus our work narrows this gap.

An interactive aggregate signature scheme allows $n$ signers, each with their own secret/public key pair $(sk_i, pk_i)$ and message $m_i$, to jointly produce a short signature that simultaneously witnesses that $m_i$ has been signed under $pk_i$ for every $i \in \{1, \dots, n\}$. Despite the large potential for savings in terms of space and verification time, which constitute the two main bottlenecks for large blockchain systems such as Bitcoin, aggregate signatures have received much less attention than the other members of the multi-party signature family, namely multi-signatures such as $\mathsf{MuSig2}$ and threshold signatures such as $\mathsf{FROST}$. In this paper, we propose $\mathsf{DahLIAS}$, the first aggregate signature scheme with constant-size signatures—a signature has the same shape as a standard Schnorr signature—directly based on discrete logarithms in pairing-free groups. The signing protocol of $\mathsf{DahLIAS}$ consists of two rounds, the first of which can be preprocessed without the message, and verification (for a signature created by $n$ signers) is dominated by one multi-exponentiation of size $n+1$, which is asymptotically twice as fast as batch verification of $n$ individual Schnorr signatures. $\mathsf{DahLIAS}$ is designed with real-world applications in mind. Besides the aforementioned benefits of space savings and verification speedups, $\mathsf{DahLIAS}$ offers key tweaking, a technique commonly used in Bitcoin to derive keys in hierarchical deterministic wallets and to save space as well as enhance privacy on the blockchain. We prove $\mathsf{DahLIAS}$ secure in the concurrent setting with key tweaking under the (algebraic) one-more discrete logarithm assumption in the random oracle model.

Constructing and implementing isogeny-based cryptographic primitives is an active research. In particular, performing length-$n$ isogenies walks over quadratic field extensions of $\mathbb{F}_p$ plays an exciting role in some constructions, including Hash functions, Verifiable Delay Functions, Key-Encapsulation Mechanisms, and generic proof systems for isogeny knowledge. Remarkably, many isogeny-based constructions, for efficiency, perform $2$-isogenies through square root calculations. This work analyzes the idea of using $3$-isogenies instead of $2$-isogenies, which replaces the requirement of calculating square roots with cube roots. Performing length-$m$ $3$-isogenies allows shorter isogeny walks than when employing length-$n$ $2$-isogenies since a cube root calculation costs essentially the same as computing a square root, and we require $3^m \approx 2^n$ to provide the same security level. We propose an efficient mapping from arbitrary supersingular Montgomery curves defined over $\mathbb{F}_{p^2}$ to the $3$-isogeny curve model from Castryck, Decru, and Vercauteren (Asiacrypt 2020); a deterministic algorithm to compute all order-$3$ points on arbitrary supersingular Montgomery curves, and an efficient algorithm to compute length-$m$ $3$-isogeny chains. We improve the length-$m$ $3$-isogeny walks required by the KEM from Nakagawa and Onuki (CRYPTO 2024) by using our results and introducing more suitable parameter sets that are friendly with C-code implementations. In particular, our experiments illustrate an improvement of 26.41\%--35.60\% in savings when calculating length-$m$ $3$-isogeny chains and using our proposed parameters instead of those proposed by Nakagawa and Onuki (CRYPTO 2024). Finally, we enhance the key generation of $\mathsf{CTIDH}$-2048 by including radical $3$-isogeny chains over the basefield $\mathbb{F}_p$, reducing the overhead of finding a $3$-torsion basis as required in some instantiations of the $\mathsf{CSIDH}$ protocol. Our experiments illustrate the advantage of radical $3$ isogenies in the key generation of $\mathsf{CTIDH}$-2048, with an improvement close to 4x faster than the original $\mathsf{dCTIDH}$.

With the increasing usage of fake videos in misinformation campaigns, proving the provenance of an edited video becomes critical, in particular, without revealing the original footage. We formalize the notion and security model of proofs of video authenticity and give the first cryptographic video authentication protocol Eva, which supports lossy codecs and arbitrary edits and is proven secure under well-established cryptographic assumptions. Compared to previous cryptographic methods for image authentication, Eva is not only capable of handling significantly larger amounts of data originating from the complex lossy video encoding but also achieves linear prover time, constant RAM usage, and constant proof size with respect to video size. These improvements have optimal theoretic complexity and are enabled by our two new theoretical advancements of integrating lookup arguments with folding-based incrementally verifiable computation (IVC) and compressing IVC proof efficiently, which may be of independent interest. For our implementation of Eva, we then integrate them with the Nova folding scheme, which we call Lova. As for concrete performance, we additionally utilize various optimizations such as tailored circuit design and GPU acceleration to make Eva highly practical: for a 2-minute HD (1280×720) video encoded in H.264 at 30 frames per second, Eva generates a 448 B proof in about 2.4 hours on consumer-grade hardware at 2.6 μs per pixel, surpassing state-of-the-art cryptographic image authentication schemes by more than an order of magnitude in terms of prover time and proof size.

Fully Homomorphic Encryption offers an effective solution for privacy-preserving computation, but its adoption is hindered by substantial computational and communication overheads. To address these, the Hybrid Homomorphic Encryption (HHE) protocol was developed, where the client encrypts data using a symmetric encryption scheme (SE), and the server homomorphically evaluates its decryption. Previous studies have demonstrated that the HHE protocol has no impact on the correctness of applications; however, in this work, we shift the focus to its security resilience when subjected to Differential Fault Analysis (DFA). While DFA has proven effective against standalone symmetric-key primitives, no DFA study has been proposed that exploits the HHE protocol as a whole. Furthermore, previous DFA approaches on SE rely on strong assumptions such as nonce reuse, which limits their applicability in real-world protocols or practical applications. In this work, we show that the structure of the HHE protocol itself exposes new avenues for fault exploitation. We introduce Sasta-DFA, which, to our knowledge, is the first DFA targeting HHE protocol in its entirety. Our study demonstrates that an attacker can achieve complete key recovery with a single fault injection. A key feature of this attack is that it does not require nonce reuse, thus adhering to nonce-related specifications. We adapt the IND-CPAD threat model proposed by Li and Micciancio at Eurocrypt’21 for HHE in the context of fault attacks. We conduct the first DFA study on the emerging HHE-specific integer-based SE schemes— Rubato, Hera, Pasta, and Masta. Notably, our attack methodology is generalizable and applicable to a broader class of HHE-friendly SE schemes, including boolean schemes like Rasta and even the standard scheme AES. We also present the first experimental validation of fault analysis on these new HHE-enabling schemes. Our attack, mounted on an ATXmega128D4-AU microcontroller, successfully demonstrates full key recovery. Finally, we also extend Sasta-DFA to Authenticated Transciphering protocols under a weaker threat model that removes any functional dependency.

The securities of a large fraction of zero-knowledge arguments of knowledge schemes rely on the discrete logarithm (DL) assumption or the discrete logarithm relation assumption, such as Bulletproofs (S&P 18) and compressed $\Sigma$-protocol (CRYPTO 20). At the heart of these protocols is an interactive proof of knowledge between a prover and a verifier showing that a Pedersen vector commitment $P=h^{\rho}\cdot\textbf{g}^{\textbf{x}}$ to a vector $\textbf{x}$ satisfies multi-variate equations, where the DL relations among the vector of generators $\textbf{g}$ are unknown. However, in some circumstances, the prover may know the DL relations among the generators, and the DL relation assumption no longer holds, such as ring signatures, ring confidential transactions (RingCT) and K-out-of-N proofs, which will make the soundness proof of these protocols infeasible. This paper is concerned with a problem called knowledge of known discrete logarithms (KKDL) that appears but has not been clearly delineated in the literature. Namely, it asks to prove a set of multi-exponent equalities, starting with the fact that the prover may know the DL relations among the generators of these equalities. Our contributions are three-fold: (1) We propose a special honest-verifier zero-knowledge protocol for the problem. Using the Fiat-Shamir heuristic and the improved inner-product argument of Bulletproofs, the proof size of our protocol is logarithmic to the dimension of the vector. (2) As applications, our protocol can be utilized to construct logarithmic-size RingCT securely which fixes the issues of Omniring (CCS 19), ring signatures (with signature size $2\cdot \lceil \log_2(N) \rceil+10$ for ring size $N$) and $K$-out-of-$N$ proof of knowledge (with proof size $2\cdot \lceil \log_2(N) \rceil+14$) which achieves the most succinct proof size improving on previous results. Meanwhile, we propose the first account-based multi-receiver privacy scheme considering the sender's privacy with logarithmic proof size (to the best of our knowledge). (3) We describe an attack on RingCT-3.0 (FC 20) where an attacker can spend a coin of an arbitrary amount that never existed on the blockchain.

In this work, we explore neural network design options for discriminating Random Number Generators(RNG), as a complement to existing statistical test suites, being a continuation of a recent paper of the aothors. Specifically, we consider variations in architecture and data preprocessing. We test their impact on the network's ability to discriminate sequences from a low-quality RNG versus a high-quality one—that is, to discriminate between "optimal" sequence sets and those from the generator under test. When the network fails to distinguish them, the test is passed. For this test to be useful, the network must have real discrimination capabilities. We review several network design possibilities showing significant differences in the obtained results. The best option presented here is convolutional networks working on 5120-byte sequences.

In this study, we introduce a new approach to secure computing by implementing a platform that utilizes a non-volatile memory express (NVMe)-based system with an FPGA-based Torus fully homomorphic encryption (TFHE) accelerator, solid state drive (SSD), and middleware on the host-side. Our platform is the first to offer completely secure computing capabilities for TFHE by using an FPGA-based accelerator. We defined secure computing instructions to evaluate 14-bit to 14-bit functions using TFHE. Our middleware allows for the communication of ciphertexts, keys, and secure computing programs while invoking secure computing programs through NVMe commands with metadata. Our performance evaluation demonstrates that our secure computing platform outperforms CPU-based and GPU-based platforms by 15 to 120 times and 2.5 to 3 times, respectively, in gate bootstrapping execution time. Additionally, our platform uses 7 to 12 times less electric energy consumption during the gate bootstrapping execution time than CPU-based platforms and 4.95 times less than a GPU-based platform. The performance of a machine learning application running on our platform shows that bootstrapping accounts for more than 80% of ciphertext learning time.

In this paper, we present Trilithium: a protocol for distributed key generation and signing compliant with FIPS 204 (ML-DSA). Our protocol allows two parties, "server" and "phone" with assistance of correlated randomness provider (CRP) to produce a standard ML-DSA signature. We prove our protocol to be secure against a malicious server or phone in the universal composability (UC) model, introducing some novel techniques to argue the security of two-party secure computation protocols with active security against one party, but only active privacy against the other. We provide an implementation of our protocol in Rust and benchmark it, showing the practicality of the protocol.

Quantum computing is regarded as one of the most significant upcoming advancements in computer science. Although fully operational quantum computers have yet to be realized, they are expected to solve specific problems that are difficult to solve using classical computers. Given the limitations of quantum computing resources, it is crucial to design compact quantum circuits for core operations, such as quantum arithmetic. In this paper, we focus on optimizing the circuit depth of quantum multi-operand addition, which is a fundamental component in quantum implementations (as an example, SHA-2). Building on the foundational quantum carry-save approach by Phil Gossett, we introduce a tree-based quantum carry-save adder. Our design integrates the Wallace and Dadda trees to optimize carry handling during multi-operand additions. To further reduce circuit depth, we utilize additional ancilla qubits for parallel operations and introduce an efficient technique for reusing these ancilla qubits. Our tree-based carry-save adder achieves the lowest circuit depth ($T$-depth) and provides an improvement of over 82% (up to 99%) in the qubit count–circuit depth product for multi-operand addition. Furthermore, we apply our method to multiplication, achieving the lowest circuit depth and an improvement of up to 87% in the qubit count–circuit depth product.

Side-channel analysis (SCA) has emerged as a critical field in securing hardware implementations against potential vulnerabilities. With the advent of artificial intelligence(AI), neural network-based approaches have proven to be among the most useful techniques for profiled SCA. Despite the success of NN-assisted SCA, a critical challenge remains, namely understanding predictive uncertainty. NNs are often uncertain in their predictions, leading to incorrect key guesses with high probabilities, corresponding to a higher rank associated with the correct key. This uncertainty stems from multiple factors, including measurement errors, randomness in physical quantities, and variability in NN training. Understanding whether this uncertainty arises from inherent data characteristics or can be mitigated through better training is crucial. Additionally, if data uncertainty dominates, identifying specific trace features responsible for misclassification becomes essential. We propose a novel approach to estimating uncertainty in NN-based SCA by leveraging Renyi entropy, which offers a generalized framework for capturing various forms of uncertainty. This metric allows us to quantify uncertainty in NN predictions and explain its impact on key recovery. We decompose uncertainty into epistemic (model-related) and aleatoric (data-related) components. Given the challenge of estimating probability distributions in high-dimensional spaces, we use matrix-based Renyi α-entropy and α-divergence to better approximate leakage distributions, addressing the limitations of KL divergence in SCA. We also explore the sources of uncertainty, e.g., resynchronization, randomized keys, as well as hyperparameters related to NN training. To identify which time instances (features in traces) contribute most to uncertainty, we also integrate SHAP explanations with our framework, overcoming the limitations of conventional sensitivity analysis. Lastly, we show that predictive uncertainty strongly correlates with standard SCA metrics like rank, offering a complementary measure for evaluating attack complexity. Our theoretical findings are backed by extensive experiments on available datasets and NN models.

The Secure Shell (SSH) protocol is one of the first security protocols on the Internet to upgrade itself to resist attacks against future quantum computers, with the default adoption of the "quantum (otherwise, classically)" secure hybrid key exchange in OpenSSH from April 2022. However, there is a lack of a comprehensive security analysis of this quantum-resistant version of SSH in the literature: related works either focus on the hybrid key exchange in isolation and do not consider security of the overall protocol, or analyze the protocol in security models which are not appropriate for SSH, especially in the "post-quantum" setting. In this paper, we remedy the state of affairs by providing a thorough post-quantum cryptographic analysis of SSH. We follow a "top-down" approach wherein we first prove security of SSH in a more appropriate model, namely, our post-quantum extension of the so-called authenticated and confidential channel establishment (ACCE) protocol security model; our extension which captures "harvest now, decrypt later" attacks could be of independent interest. Then we establish the cryptographic properties of SSH's underlying primitives, as concretely instantiated in practice, based on our protocol-level ACCE security analysis: for example, we prove relevant cryptographic properties of "Streamlined NTRU Prime", a key encapsulation mechanism (KEM) which is used in recent versions of OpenSSH and TinySSH, in the quantum random oracle model, and address open problems related to its analysis in the literature. Notably, our ACCE security analysis of post-quantum SSH relies on the weaker notion of IND-CPA security of the ephemeral KEMs used in the hybrid key exchange. This is in contrast to prior works which rely on the stronger assumption of IND-CCA secure ephemeral KEMs. Hence we conclude the paper with a discussion on potentially replacing IND-CCA secure KEMs in current post-quantum implementations of SSH with simpler and faster IND-CPA secure counterparts, and also provide the corresponding benchmarks.

Hedged PKE schemes are designed to provide useful security when the per-message randomness fails to be uniform, say, due to faulty implementations or adversarial actions. A simple and elegant theoretical approach to building such schemes works like this: Synthesize fresh random bits by hashing all of the encryption inputs, and use the resulting hash output as randomness for an underlying PKE scheme. The idea actually goes back to the Fujisaki-Okamoto transform for turning CPA-secure encryption into CCA-secure encryption, and is also used to build deterministic PKE schemes. In practice, implementing this simple construction is surprisingly difficult, as the high- and mid-level APIs presented by the most commonly used crypto libraries (e.g. OpenSSL and forks thereof) do not permit one to specify the per-encryption randomness. Thus application developers are forced to piece together low-level functionalities and attend to any associated, security-critical algorithmic choices. Other approaches to hedged PKE present similar problems in practice. We reconsider the matter of building hedged PKE schemes, and the security notions they aim to achieve. We lift the current best-possible security notion for hedged PKE (IND-CDA) from the CPA setting to the CCA setting, and then show how to achieve it using primitives that are readily available from high-level APIs. We also propose a new security notion, MM-CCA, which generalizes traditional IND-CCA to admit imperfect randomness. Like IND-CCA, and unlike IND-CDA, our notion gives the adversary the public key. We show that MM-CCA is achieved by RSA-OAEP in the random-oracle model; this is significant in practice because RSA-OAEP is directly available from high-level APIs across all libraries we surveyed. We sort out relationships among the various notions, and also develop new results for existing hedged PKE constructions.

A multi-server private information retrieval (PIR) protocol allows a client to obtain an entry of its choice from a database, held by one or more servers, while hiding the identity of the entry from small enough coalitions of servers. In this paper, we study PIR protocols in which some of the servers are malicious and may not send messages according to the pre-described protocol. In previous papers, such protocols were defined by requiring that they are correct, private, and robust to malicious servers, i.e., by listing 3 properties that they should satisfy. However, 40 years of experience in studying secure multiparty protocols taught us that defining the security of protocols by a list of required properties is problematic. In this paper, we rectify this situation and define the security of PIR protocols with malicious servers using the real vs. ideal paradigm. We study the relationship between the property-based definition of PIR protocols and the real vs. ideal definition, showing the following results: - We prove that if we require full security from PIR protocols, e.g., the client outputs the correct value of the database entry with high probability even if a minority of the servers are malicious, then the two definitions are equivalent. This implies that constructions of such protocols that were proven secure using the property-based definition are actually secure under the ``correct'' definition of security. - We show that if we require security-with-abort from PIR protocols (called PIR protocols with error-detection in previous papers), i.e., protocols in which the user either outputs the correct value or an abort symbol, then there are protocols that are secure under the property-based definition; however, they do not satisfy the real vs. ideal definition, that is, they can be attacked allowing selective abort. This shows that the property-based definition of PIR protocols with security-with-abort is problematic. - We consider the compiler of Eriguchi et al. (TCC 22) that starts with a PIR protocol that is secure against semi-honest servers and constructs a PIR protocol with security-with-abort; this compiler implies the best-known PIR protocols with security-with-abort. We show that applying this protocol does not result in PIR protocols that are secure according to the real vs. ideal definition. However, we prove that a simple modification of this compiler results in PIR protocols that are secure according to the real vs. ideal definition.

Since the standardization of the Secure Group Messaging protocol Messaging Layer Security (MLS) [4 ], whose core subprotocol is a Continuous Group Key Agreement (CGKA) mechanism named TreeKEM, CGKAs have become the norm for group key exchange protocols. However, in order to alleviate the security issue originating from the fact that all users in a CGKA are able to carry out sensitive operations on the member group, an augmented protocol called Administrated-CGKA (A-CGKA) has been recently created [2]. An A-CGKA includes in the cryptographic protocol the management of the administration rights that restrict the set of privileged users, giving strong security guarantees for the group administration. The protocol designed in [2] is a plugin added to a regular (black-box) CGKA, which consequently add some complexity to the underlying CGKA and curtail its performances. Yet, leaving the fully decentralized paradigm of a CGKA offers the perspective of new protocol designs, potentially more efficient. We propose in this paper an A-CGKA called SUMAC, which offers strongly enhanced communication and storage performances compared to other A-CGKAs and even to TreeKEM. Our protocol is based on a novel design that modularly combines a regular CGKA used by the administrators of the group and a Tree-structured Multicast Key Agreement (TMKA) [9] – which is a centralized group key exchange mechanism administrated by a single group manager – between each administrator and all the standard users. That TMKA gives SUMAC an asymptotic communication cost logarithmic in the number of users, similarly to a CGKA. However, the concrete performances of our protocol are much better than the latter, especially in the post-quantum framework, due to the intensive use of secret-key cryptography that offers a lighter bandwidth than the public-key encryption schemes from a CGKA. In practice, SUMAC improves the communication cost of TreeKEM by a factor 1.4 to 2.4 for admin operations and a factor 2 to 38 for user operations. Similarly, its storage cost divides that of TreeKEM by a factor 1.3 to 23 for an administrator and 3.9 to 1,070 for a standard user. Our analysis of SUMAC is provided along with a ready-to-use open-source rust implementation that confirms the feasibility and the performances of our protocol.

As one of the famous quantum algorithms, Simon's algorithm enables the efficient derivation of the period of periodic functions in polynomial time. However, the complexity of constructing periodic functions has hindered the widespread application of Simon's algorithm in symmetric-key cryptanalysis. Currently, aside from the exhaustive search-based testing method introduced by Canale et al. at CRYPTO 2022, there is no unified model for effectively searching for periodic distinguishers. Although Xiang et al. established a link between periodic function and truncated differential theory at ToSC 2024, their approach lacks the ability to construct periods using unknown differentials and does not provide automated tools. This limitation underscores the inadequacy of existing methods in identifying periodic distinguishers for complex structures. In this paper, we address the challenge of advancing periodic distinguishers for symmetric-key ciphers. First, we propose a more generalized theory for constructing periodic distinguishers, addressing the limitations of Xiang et al.'s theory in handling unknown differences. We further extend our theory to probabilistic periodic distinguishers, thereby extending the separability property proposed by Hodžić et al. in 2020. As a result, our theory can cover a wider range of periodic distinguishers. Second, we introduce a novel symbolic representation to simplify the search of periodic distinguishers. Based upon this representation, we propose the first fully automated SMT-based search model, which efficiently addresses the challenges of manual searching in complex structures. Finally, we extend the model to SPN structures based on our new theory. Our model has broad applicability through significant advancements in analyzing generalized Feistel structures (GFSs) and SPN-based ciphers. As a general model, we have achieved new quantum distinguishers with the following round configurations: 10 rounds for GFS-4F, 10 rounds for LBlock, 10 rounds for TWINE, and 16 rounds for Skipjack-B, improving the previous best results by 2, 2, 2, and 3 rounds, respectively. In the domain of SPN-based ciphers, our model has enabled the identification of novel periodic distinguishers, including the first 9-round distinguisher for SKINNY and the first 12-round distinguisher for CRAFT. These achievements lay the foundation for quantum cryptanalysis of SPN-based ciphers using Simon’s algorithm.

Private information retrieval (PIR) allows a client to query a public database privately and serves as a key building block for privacy-enhancing applications. Minimizing query size is particularly important in many use cases, for example when clients operate on low-power or bandwidth-constrained devices. However, existing PIR protocols exhibit large query sizes: to query $2^{25}$ records, the smallest query size of 14.8KB is reported in Respire [Burton et al., CCS'24]. Respire is based on fully homomorphic encryption (FHE), where a common approach to lower the client-to-server communication cost is transciphering. When combining the state-of-the-art transciphering [Bon et al., CHES'24] with Respire, the resulting protocol (referred to as T-Respire) has a 336B query size, while incurring a 16.2x times higher server computation cost than Respire. Our work presents the Pirouette protocol, which achieves a query size of just 36B without transciphering. This represents a 9.3x reduction compared to T-Respire and a 420x reduction to Respire. For queries over $2^{25}$ records, the single-core server computation in Pirouette is only 2x slower than Respire and 8.1x faster than T-Respire, and the server computation is highly parallelizable. Furthermore, Pirouette requires no database-specific hint for clients and naturally extends to support queries over encrypted databases.

Simple power analysis (SPA) attacks and their extensions, profiled and soft-analytical side-channel attacks (SASCA), represent a significant threat to the security of cryptographic devices and remain among the most powerful classes of passive side-channel attacks. In this work, we analyze how numeric representations of secrets can affect the amount of exploitable information leakage available to the adversary. We present an analysis of how mutual information changes as a result of the integer ring size relative to the machine word-size. Furthermore, we study the Redundant Number Representation (RNR) countermeasure and show that its application to ML-KEM can resist the most powerful SASCA attacks and provides a low-cost alternative to shuffling. We eval- uate the performance of RNR-ML-KEM with both simulated and prac- tical SASCA experiments on the ARM Cortex-M4 based on a worst-case attack methodology. We show that RNR-ML-KEM sufficiently renders these attacks ineffective. Finally, we evaluate the performance of the RNR-ML-KEM NTT and INTT and show that SPA security can be achieved with a 62.8% overhead for the NTT and 0% overhead for the INTT relative to the ARM Cortex-M4 reference implementation used.

Quantum Key Distribution (QKD) is currently being discussed as a technology to safeguard communication in a future where quantum computers compromise traditional public-key cryptosystems. In this paper, we conduct a comprehensive security evaluation of QKD-based solutions, focusing on real-world use cases sourced from academic literature and industry reports. We analyze these use cases, assess their security and identify the possible advantages of deploying QKD-based solutions. We further compare QKD-based solutions with Post-Quantum Cryptography (PQC), the alternative approach to achieving security when quantum computers compromise traditional public-key cryptosystems, evaluating their respective suitability for each scenario. Based on this comparative analysis, we critically discuss and comment on which use cases QKD is suited for, considering factors such as implementation complexity, scalability, and long-term security. Our findings contribute to a better understanding of the role QKD could play in future cryptographic infrastructures and offer guidance to decision-makers considering the deployment of QKD.

Matrix multiplication of two encrypted matrices (CC-MM) is a key challenge for privacy-preserving machine learning applications. As modern machine learning models focus on scalability, fast CC-MM on large datasets is increasingly in demand. In this work, we present a CC-MM algorithm for large matrices. The algorithm consists of plaintext matrix multiplications (PP-MM) and ciphertext matrix transpose algorithms (C-MT). We propose a fast C-MT algorithm, which is computationally inexpensive compared to PP-MM. By leveraging high-performance BLAS libraries to optimize PP-MM, we implement large-scale CC-MM with substantial performance improvements. Furthermore, we propose lightweight algorithms, significantly reducing the key size from $1\ 960$ MB to $1.57$ MB for CC-MM with comparable efficiency. In a single-thread implementation, the C-MT algorithm takes $0.76$ seconds to transpose a $2\ 048\times 2\ 048$ encrypted matrix. The CC-MM algorithm requires $85.2$ seconds to multiply two $4\ 096\times 4\ 096$ encrypted matrices. For large matrices, our algorithm outperforms the state-of-the-art CC-MM method from Jiang-Kim-Lauter-Song [CCS'18] by a factor of over $800$.

Typical protocols in the multi-party private set operations (MPSO) setting enable $m > 2$ parties to perform certain secure computation on the intersection or union of their private sets, realizing a very limited range of MPSO functionalities. Most works in this field focus on just one or two specific functionalities, resulting in a large variety of isolated schemes and a lack of a unified framework in MPSO research. In this work, we present an MPSO framework, which allows $m$ parties, each holding a set, to securely compute any set formulas (arbitrary compositions of a finite number of binary set operations, including intersection, union and difference) on their private sets. Our framework is highly versatile and can be instantiated to accommodate a broad spectrum of MPSO functionalities. To the best of our knowledge, this is the first framework to achieve such a level of flexibility and generality in MPSO, without relying on generic secure multi-party computation (MPC) techniques. Our framework exhibits favorable theoretical and practical performance. With computation and communication complexity scaling linearly with the set size $n$, it achieves optimal complexity that is on par with the naive solution for widely used functionalities, such as multi-party private set intersection (MPSI), MPSI with cardinality output (MPSI-card), and MPSI with cardinality and sum (MPSI-card-sum), for the first time in the standard semi-honest model. Furthermore, the instantiations of our framework, which primarily rely on symmetric-key techniques, provide efficient protocols for MPSI, MPSI-card, MPSI-card-sum, and multi-party private set union (MPSU), with online performance that either surpasses or matches the state of the art in standard semi-honest model. At the technical core of our framework is a newly introduced primitive called predicative zero-sharing. This primitive captures the universality of a number of MPC protocols and is composable. We believe it may be of independent interest.

Multi-party private set union (MPSU) protocol enables $m$ $(m > 2)$ parties, each holding a set, to collectively compute the union of their sets without revealing any additional information to other parties. There are two main categories of multi-party private set union (MPSU) protocols: The first category builds on public-key techniques, where existing works require a super-linear number of public-key operations, resulting in poor practical efficiency. The second category builds on oblivious transfer and symmetric-key techniques. The only work in this category, proposed by Liu and Gao (ASIACRYPT 2023), features the best concrete performance among all existing protocols, but still has super-linear computation and communication. Moreover, it does not achieve the standard semi-honest security, as it inherently relies on a non-collusion assumption, which is unlikely to hold in practice. There remain two significant open problems so far: no MPSU protocol achieves semi-honest security based on oblivious transfer and symmetric-key techniques; no MPSU protocol achieves both linear computation and linear communication complexity. In this work, we resolve both of them. - We propose the first MPSU protocol based on oblivious transfer and symmetric-key techniques in the standard semi-honest model. This protocol's online performance is $3.9-10.0 \times$ faster than Liu and Gao in the LAN setting. Concretely, our protocol requires only $4.4$ seconds in online phase for $3$ parties with sets of $2^{20}$ items each. - We propose the first MPSU protocol achieving linear computation and linear communication complexity, based on public-key operations. This protocol has the best total performance in the WAN settings, due to a factor of $3.0-36.5\times$ improvement in terms of overall communication compared to Liu and Gao. Concretely, on slow network ($50$ Mbps), their protocol takes $6.6$ hours to run for $9$ parties with sets of $2^{18}$ items each, whereas ours only takes $47$ minutes. We implement our protocols and conduct extensive experiments to compare the performance of our protocols and the state-of-the-art. To the best of our knowledge, our code is the first correct and secure implementation of MPSU that reports on large-size experiments.

The question of whether the complexity class P equals NP is a major unsolved problem in theoretical computer science. The key to proving that P $\neq$ NP is to show that there is no efficient (polynomial time) algorithm for a language in NP. For a language in NP, it is impossible to prove that it is not in P, because we can only claim that no better algorithm has been found so far, and there is no way to guarantee (or prove) that a more efficient algorithm does not exist. It is impossible to prove P $\neq$ NP rigorously, as any problem with size $n$ and solution space $2^n$ has certain structures and properties, and there is no way to prove that more efficient algorithms that take advantage of these structures or properties do not exist. In all attempts to prove P $\neq$ NP, all we can do is try to provide the best clues or "evidence" for P $\neq$ NP. In this paper, we introduce a new language, the Add/XNOR problem, which has the simplest structure and perfect randomness, by extending the subset sum problem. We conjecture that the square-root time complexity is required to solve the Add/XNOR problem, making it surpass the subset sum problem as the latter has algorithms that break the square-root complexity bound, a better evidence for P $\neq$ NP. Furthermore, by giving up commutative and associative properties, we design a magma equipped with a permutation and successfully achieve Conjecture 2, which is the first problem with exponential complexity that is believed to require an exhaustive search to solve, by far the strongest evidence for P $\neq$ NP.

At ASIACRYPT’19, Bonnetain et al. demonstrated that an S-box can be distinguished from a permutation chosen uniformly at random by quantifying the distances between their behaviors. In this study, we extend this approach by proposing a deep learning-based method to quantify distances between two different S-boxes and evaluate similarities in their design structures. First, we introduce a deep learning-based framework that trains a neural network model to recover the design structure of a given S-box based on its cryptographic table. We then interpret the decision-making process of our trained model to analyze which coefficients in the table play significant roles in identifying S-box structures. Additionally, we investigate the inference results of our model across various scenarios to evaluate its generalization capabilities. Building upon these insights, we propose a novel approach to quantify distances between structurally different S-boxes. Our method effectively assesses structural similarities by embedding S-boxes using the deep learning model and measuring the distances between their embedding vectors. Furthermore, experimental results confirm that this approach is also applicable to structures that the model has never seen during training. Our findings demonstrate that deep learning can reveal the underlying structural similarities between S-boxes, highlighting its potential as a powerful tool for S-box reverse-engineering.

In this work, we introduce ToFA, the first fault attack (FA) strategy that attempts to leverage the classically well-known idea of impossible differential cryptanalysis to mount practically verifiable attacks on bit-oriented ciphers like GIFT and BAKSHEESH. The idea used stems from the fact that truncated differential paths induced due to fault injection in certain intermediate rounds of the ciphers lead to active SBox-es in subsequent rounds whose inputs admit specific truncated differences. This leads to a (multi-round) impossible differential distinguisher, which can be incrementally leveraged for key-guess elimination via partial decryption. The key-space reduction further exploits the multi-round impossibility, capitalizing on the relations due to the quotient-remainder (QR) groups of the GIFT and BAKSHEESH linear layer, which increases the filtering capability of the distinguisher. Moreover, the primary observations made in this work are independent of the actual SBox. Clock glitch based fault attacks were mounted on 8-bit implementations of GIFT-64/GIFT-128 using a ChipWhisperer Lite board on an 8-bit ATXmega128D4-AU micro-controller. Unique key recovery was achieved for GIFT-128 with 3 random byte faults, while for GIFT-64, key space was reduced to $2^{32}$, the highest achievable for GIFT-64, with a single level fault due to its key-schedule. This work also reports the highest fault injection penetration for any variant of GIFT and BAKSHEESH. Finally, this work reiterates the role of classical cryptanalysis strategies in fault vulnerability assessment while leading to the most efficient fault attacks on GIFT.

Impossible differential attack is one of the major cryptanalytical methods for symmetric-key block ciphers. In this paper, we evaluate the security of SAND-128 against impossible differential attack. SAND is an AND-RX-based lightweight block cipher proposed by Chen et al. in Designs, Codes and Cryptography 2022. There are two variants of SAND, namely SAND-64 and SAND-128, due to structural differences. In this paper, we search for impossible differential distinguishers of SAND-128 using the Constraint Programming (CP) and reveal 14-round impossible differential distinguishers. The number of 14-round distinguishers is $2^{14} \times 7 = 114,688$. Furthermore, we demonstrate a key recovery attack on 21-round SAND-128. The complexities for the attack require $2^{124}$ data, $2^{127.2}$ encryptions, and $2^{122}$ bytes of memory, respectively. Although this result currently achieves the best attack on round-reduced SAND-128, this attack does not threaten the security of SAND-128 against impossible differential attack.

Despite decades of effort, a chasm existed between the theory and practice of device-level biometric authentication. Deployed authentication algorithms rely on data that overtly leaks private information about the biometric; thus systems rely on externalized security measures such as trusted execution environments. The authentication algorithms have no cryptographic guarantees. We close this chasm. We introduce a key derivation system with 105 bits of entropy and a 91% true accept rate for the iris. Our system advances 1) the feature extraction from the iris and 2) the fuzzy extractor used to derive keys. The fuzzy extractor builds on sample-then-lock (Canetti et al., Journal of Cryptology 2021). We 1) Introduce a new method of sampling that achieves a better TAR versus entropy tradeoff when features have different quality, 2) Correct their security proof, showing the minimum of min-entropy of subsets is the relevant security measure, and 3) Tighten their concrete analysis, nearly doubling security under reasonable assumptions. Our final feature extractor incorporates ideas from the new sampling method to produce features optimized for the sample-then-lock construction. The only statistical assumption needed to show security of our system is necessary: the accuracy of min-entropy estimation. Our quantitive level of security is well above prior work. Simhadri et al. (ISC, 2019) report $32$ bits on the iris, but they have a bug in their analysis (that we fix) that reduces their strength. Zhang et al.'s (ePrint 2021/1559) system achieves $45$ bits on the face but assumes independence between biometrics and the used error-correcting code, an assumption that cannot be easily verified. Other prior work assumes that bits of biometrics are i.i.d., an assumption that is demonstrably false. (Or that all correlation is pairwise between features (Hine et al., TIFS 2023).) Irises used to evaluate TAR and security are class disjoint from those used for training and collecting statistics (the open dataset regime).

M. Dyakonov [IEEE Spectrum, 2019] asked: what precision is required for manipulating a quantum gate, and what role is the notion of ENERGY playing in quantum computing theory. We answer the questions by investigating the Quantum Fourier Transformation (QFT). We show that the precision for a qubit operation is no less than $4.72694\times 10^{-36}$, in accordance with the energy of a free particle. Quantum entanglement is indispensable to quantum supremacy. The present quantum computers have failed to instantiate quantum entanglement up to our expectation, due to inexact qubit operations. Quantum transition incurred during the transition of space-time continuum covertly changes qubits and corrupts quantum supremacy.

Verifying image provenance has become an important topic, especially in the realm of news media. To address this issue, the Coalition for Content Provenance and Authenticity (C2PA) developed a standard to verify image provenance that relies on digital signatures produced by cameras. However, photos are usually edited before being published, and a signature on an original photo cannot be verified given only the published edited image. In this work, we describe VerITAS, a system that uses zero-knowledge proofs (zk-SNARKs) to prove that only certain edits have been applied to a signed photo. While past work has created image editing proofs for photos, VerITAS is the first to do so for realistically large images (30 megapixels). Our key innovation enabling this leap is the design of a new proof system that enables proving knowledge of a valid signature on a large amount of witness data. We run experiments on realistically large images that are more than an order of magnitude larger than those tested in prior work. In the case of a computationally weak signer, such as a camera, we are able to generate a proof of valid edits for a 90 MB image in just over thirteen minutes, costing about $0.54 on AWS per image. In the case of a more powerful signer, we are able to generate a proof of valid edits for a 90 MB image in just over three minutes, costing only \$0.13 on AWS per image. Either way, proof verification time is less than a second. Our techniques apply broadly whenever there is a need to prove that an efficient transformation was applied correctly to a large amount of signed private data.

Fundamental principles of quantum mechanics have inspired many new research directions, particularly in quantum cryptography. One such principle is quantum no-cloning which has led to the emerging field of revocable cryptography. Roughly speaking, in a revocable cryptographic primitive, a cryptographic object (such as a ciphertext or program) is represented as a quantum state in such a way that surrendering it effectively translates into losing the capability to use this cryptographic object. All of the revocable cryptographic systems studied so far have a major drawback: the recipient only receives one copy of the quantum state. Worse yet, the schemes become completely insecure if the recipient receives many identical copies of the same quantum state---a property that is clearly much more desirable in practice. While multi-copy security has been extensively studied for a number of other quantum cryptographic primitives, it has so far received only little treatment in context of unclonable primitives. Our work, for the first time, shows the feasibility of revocable primitives, such as revocable encryption and revocable programs, which satisfy multi-copy security in oracle models. This suggest that the stronger notion of multi-copy security is within reach in unclonable cryptography more generally, and therefore could lead to a new research direction in the field.

Random classical codes have good error correcting properties, and yet they are notoriously hard to decode in practice. Despite many decades of extensive study, the fastest known algorithms still run in exponential time. The Learning Parity with Noise (LPN) problem, which can be seen as the task of decoding a random linear code in the presence of noise, has thus emerged as a prominent hardness assumption with numerous applications in both cryptography and learning theory. Is there a natural quantum analog of the LPN problem? In this work, we introduce the Learning Stabilizers with Noise (LSN) problem, the task of decoding a random stabilizer code in the presence of local depolarizing noise. We give both polynomial-time and exponential-time quantum algorithms for solving LSN in various depolarizing noise regimes, ranging from extremely low noise, to low constant noise rates, and even higher noise rates up to a threshold. Next, we provide concrete evidence that LSN is hard. First, we show that LSN includes LPN as a special case, which suggests that it is at least as hard as its classical counterpart. Second, we prove a worst-case to average-case reduction for variants of LSN. We then ask: what is the computational complexity of solving LSN? Because the task features quantum inputs, its complexity cannot be characterized by traditional complexity classes. Instead, we show that the LSN problem lies in a recently introduced (distributional and oracle) unitary synthesis class. Finally, we identify several applications of our LSN assumption, ranging from the construction of quantum bit commitment schemes to the computational limitations of learning from quantum data.

The Messaging Layer Security (MLS) protocol, recently standardized in RFC 9420, aims to provide efficient asynchronous group key establishment with strong security guarantees. The main component of MLS, which is the source of its key efficiency and security properties, is a protocol called TreeKEM. Given that a major vision for the MLS protocol is for it to become the new standard for messaging applications like WhatsApp, Facebook Messenger, Signal, etc., it has the potential to be used by a huge number of users. Thus, it is important to better understand the security of MLS and hence also of TreeKEM. In previous work, TreeKEM was proven adaptively secure in the Random Oracle Model (ROM) with a polynomial loss in security by proving a result about the security of an arbitrary IND-CPA secure public-key encryption scheme in a public-key version of a security game called GSD. Unfortunately, the concrete security guarantees implied by this line of work are not sufficient for parameters used in practice. In this work, we prove a tighter bound for the security of TreeKEM when DHIES is used for public-key encryption; DHIES is currently the only standardized scheme in MLS. Our bound implies meaningful security guarantees even for small practical parameters. We follow the above approach and first introduce a modified version of the public-key GSD game better suited for analyzing TreeKEM. We then provide a simple and detailed proof of security for DHIES in this game in the ROM and achieve a smaller security loss compared to the previous best result. Finally, we state the result on the security of TreeKEM implied by this bound and give an interpretation of the result with protocol parameters used in practice.

The paper analyzes the security of two recently proposed code-based cryptosystems that employ encryption of the form $y = m G_{\text{pub}} + eE_{pub}$: the Krouk-Kabatiansky-Tavernier (KKT) cryptosystem and the Lau-Ivanov-Ariffin-Chin-Yap (LIACY) cryptosystem. We demonstrate that the KKT cryptosystem can be reduced to a variant of the McEliece scheme, where a small set of columns in the public generator matrix is replaced with random ones. This reduction implies that the KKT cryptosystem is vulnerable to existing attacks on Wieschebrink's encryption scheme, particularly when Generalized Reed-Solomon (GRS) codes are used. In addition, we present a full key-recovery attack on the LIACY cryptosystem by exploiting its linear-algebraic structure and leveraging distinguishers of subcodes of GRS codes. Our findings reveal critical vulnerabilities in both systems, effectively compromising their security despite their novel designs.

The dual attacks on the Learning With Errors (LWE) problem are currently a subject of controversy. In particular, the results of [Matzov,2022], which claim to significantly lower the security level of CRYSTALS-Kyber, a lattice-based cryptosystem currently being standardized by NIST, are not widely accepted. The analysis behind their attack depends on a series of assumptions that, in certain scenarios, have been shown to contradict established theorems or well-tested heuristics [Ducas,Pulles,CRYPTO2023]. In this paper, we introduce a new dual lattice attack on LWE, drawing from ideas in coding theory. Our approach revisits the dual attack proposed by [Matzov,2022], replacing modulus switching with an efficient decoding algorithm. This decoding is achieved by generalizing polar codes over $\mathbb{Z}_{q}$, and we confirm their strong distortion properties through benchmarks. This modification enables a reduction from small-LWE to plain-LWE, with a notable decrease in the secret dimension. Additionally, we replace the enumeration step in the attack by assuming the secret is zero for the portion being enumerated, iterating this assumption over various choices for the enumeration part. We make an analysis of our attack without using the flawed independence assumptions used in [Matzov,2022] and we fully back up our analysis with experimental evidences. Lastly, we assess the complexity of our attack on CRYSTALS-Kyber; showing that the security levels for Kyber-512/768/1024 are 3.5/11.9/12.3 bits below the NIST requirements (143/207/272 bits) in the same nearest-neighbor cost model as in the Kyber submission. All in all the cost of our attack matches and even slightly beat in some cases the complexities originally claimed by the attack of [Matzov,2022].

As artificial intelligence plays an increasingly important role in decision-making within critical infrastructure, ensuring the authenticity and integrity of neural networks is crucial. This paper addresses the problem of detecting cloned neural networks. We present a method for identifying clones that employs a combination of metrics from both the information and physical domains: output predictions, probability score vectors, and power traces measured from the device running the neural network during inference. We compare the effectiveness of each metric individually, as well as in combination. Our results show that the effectiveness of both the information and the physical domain metrics is excellent for a clone that is a near replica of the target neural network. Furthermore, both the physical domain metric individually and the hybrid approach outperformed the information domain metrics at detecting clones whose weights were extracted with low accuracy. The presented method offers a practical solution for verifying neural network authenticity and integrity. It is particularly useful in scenarios where neural networks are at risk of model extraction attacks, such as in cloud-based machine learning services.