Steganography studies methods to not only protect the confidentiality of messages but also to conceal the very act of message transmission. Prior provably secure stegosystems are predominantly constructed based on a rejection sampling technique which achieves an encoding rate inversely proportional to the min-entropy of the cover channel. Furthermore, while replayable chosen-covertext attack (RCCA) secure stegosystems for general channels can be constructed based on standard cryptographic assumptions, it is known [Berndt and Liśkiewicz, EUROCRYPT'18] that achieving (standard) CCA-security for channels with memory in the so-called non-look-ahead model is in general impossible and the only known CCA-secure construction crucially relies on the channels being memoryless. In this work, we show that the impossibility on CCA-secure stegosystems can be circumvented, in the random oracle model, by dropping the non-look-ahead restriction and by restricting to a natural class of channels which we call "partially sampleable channels". These capture channels which partly consist of explicitly sampleable distributions, such as Gaussian sensor noise of digital photographs. To achieve a high encoding rate, we extend the formalisation of stegosystems to capture a technique known as "cover-source switching" in the practical steganography literature. This allows us to construct CCA-secure stegosystems for Gaussian channels using Gaussian preimage sampling techniques borrowed from lattice-based cryptography, which can theoretically achieve an embedding rate of $1/\omega(\log \log \lambda)$ regardless of the min-entropy of the channel. Our prototype implementation suggests that our scheme is practical, achieving an embedding rate of 24.7% in 24-megapixel RAW images in around 1 minute per image.

In this paper, we propose Dialga, a family of low-latency tweakable block ciphers designed to support 128/256-bit tweaks and 256-bit keys. Dialga achieves significantly small latency by leveraging multiple novel strategies. These include the use of multiple linear layers with efficient cell permutations, which enhance security against differential and linear attacks with negligible hardware overhead. We also identify the optimal choice of S-boxes for these permutations using state-of-the-art evaluation methods by SAT, enabling us to further reduce the delay of the round function. Besides, we design a reflection tweakey schedule that ensures strong security in the related-tweak setting and allows for encryption and decryption without delay overhead, reducing the circuit area. We conducted comprehensive hardware benchmarks involving Dialga and other primitives. As a result, Dialga achieves nearly half the delay of QARMAv2, while achieving approximately a 40% reduction in area, with the same claimed security.  We also demonstrate that Dialga enables an efficient low-latency TBC-based authenticated encryption instantiation: Flat-ΘCB based on Dialga compares favorably with AES-256-GCM in hardware, achieves substantially lower delay than AES-256-GCM.

In this work, we propose Hyperelliptic Gluing Isogeny Diffie– Hellman (HGIDH), a key-exchange protocol built from gluing isogenies between the product of two supersingular elliptic curves and the Jacobian of a genus-2 hyperelliptic curve. The protocol leverages the Frey–Kani correspondence, using maximal isotropic subgroups of (E1 × E2)[N] to construct principally polarized abelian surfaces. Private keys are encoded as four scalars defining a non-cyclic, two-dimensional kernel, thereby avoiding the structural weaknesses exploited in SIDH-style attacks. We formalize the computational tasks underlying attacks on HGIDH through two intermediate problem formulations, which abstract the recovery of gluing kernels and the computation of genus-2 isogenies. We show that any efficient adversary solving these problems can be transformed into an algorithm solving standard supersingular isogeny problems, situating the security of HGIDH within the established hardness landscape. Furthermore, we analyze the resistance of the construction to known classical and quantum attacks, including torsion-point attacks and Costello–Smith-style meet-in-the-middle strategies.

This short note explains how the Tate pairing can be used to efficiently sample torsion points with precise requirements, and other applications. These applications are most clearly explained on Montgomery curves, using the Tate pairing of degree 2, but hold more generally for any degree or abelian variety, or even generalized Tate pairings. This note is explanatory in nature; it does not contain new results, but aims to provide a clear and concise explanation of results in the literature that are somewhat hidden, yet are extremely useful in practical isogeny-based cryptography.

In this work, we present Functional Encryption (FE) schemes for Attribute-Weighted Sums (AWS), introduced by Abdalla, Gong and Wee (Crypto 2020) in the registration-based setting (RFE). In such a setting, users sample their own public/private key pairs $(\mathsf{pk}_i, \mathsf{sk}_i)$; a key curator registers user public keys along with their functions $h_i$; encryption takes as input $N$ attribute-value pairs $\{\vec x_\ell, \vec z_\ell\}_{\ell\in[N]}$ where $\vec x_\ell$ is public and $\vec z_\ell$ is private; and decryption recovers the weighted sum $\sum_{\ell\in[N]}h_i(\vec x_\ell)^\mathsf{T}\vec z_\ell$ while leaking no additional information about $\vec z_\ell$. Recently, Agrawal, Tomida and Yadav (Crypto 2023) studied the attribute-based case of AWS (AB-AWS) providing fine-grained access control, where the function is described by a tuple $(g_i, h_i)$, the input is extended to $(\vec y, \{\vec x_\ell, \vec z_\ell\}_{\ell \in [N]})$ and decryption recovers the weighted sum only if $g_i(\vec y) = 0$. Our main results are the following: - We build the first RFE for (AB-)1AWS functionality, where $N=1$, that achieves adaptive indistinguishability-based security under the (bilateral) $k$-Lin assumption in prime-order pairing groups. Prior works achieve RFE for linear and quadratic functions without access control in the standard model, or for attribute-based linear functions in the generic group model. - We develop the first RFE for AB-AWS functionality, where $N$ is unbounded, that achieves very selective simulation-based security under the bilateral $k$-Lin assumption. Here, “very selective” means that the adversary declares challenge attribute values, all registered functions and corrupted users upfront. Previously, SIM-secure RFEs were only constructed for linear and quadratic functions without access control in the same security model. We devise a novel nested encoding mechanism that facilitates achieving attribute-based access control and unbounded inputs in the registration-based setting for AWS functionalities, proven secure in the standard model. In terms of efficiency, our constructions feature short public parameters, secret keys independent of $N$, and compact ciphertexts unaffected by the length of public inputs. Moreover, as required by RFE properties, all objective sizes and algorithm costs scale poly-logarithmically with the total number of registered users in the system.

Standard symmetric encryption schemes, such as AES, other block ciphers and their modes, and stream ciphers, are highly effective and efficient for many standard scenarios. All of them have been derived from Shannon's 1948 seminal work on the communication theory of secrecy systems. Here we look at other settings where the situation is somewhat different from the standard one: \textit{e}.\textit{g}., while the encryption process may fail to update the ciphertext a limited number of times, or bits of the ciphertext are omitted: can the decryption process nevertheless recover the message in its entirety? Another situation is when encrypting a bulk of messages that must be packed together within the same dedicated ciphertext space (i.e., encryption done holographically on a clockchain space). Can a process compress the messages this way? Another issue is adding a further hiding layer to ciphertexts, like hiding the number of messages packed together, or even attempting to hide that encryption (rather than another cryptographic protocol) takes place? Can the new paradigm be based directly on a simple cryptographic (preferably post-quantum) tool? Note that the above scenarios, involving data compression and correction, are naturally derived from Shannon's other 1948 seminal work on Information Theory.   This paper introduces Encryption via Hash (EvH), a A new symmetric randomized cipher built upon a pseudorandom keyed cryptographic hash (i.e., Message Authentication Code, MAC functions), and Bloom Filters. EvH's core novelty lies in its prefix decryption capability. This unique property enables a paradigm in which encryption is tightly integrated with online compression and robust resilience to omission errors of the encryption process. By representing message prefixes in a Bloom filter, EvH allows a receiver to decrypt the initial part of a message even if subsequent data are lost, and to recover from some prefix omissions during encryption. At times, these built-in new properties may be significant (even beyond the above examples). Furthermore, this prefix-based approach facilitates simultaneous compression during the decryption phase by dynamically pruning invalid message continuations, using shared $\mu$-gram dictionaries or employing search via Large Language Models (LLMs). The result is a stateless and parallelizable cipher that, while computationally distinct from traditional ciphers, offers unique functional benefits for specific use cases, at the cost of correctness being ensured only probabilistically (as in compression processes), though the error can be well controlled and made significantly small.

The use of biometric-based security protocols is on the steep rise. As biometrics become more popular, we witness more attacks. For example, recent BrutePrint/InfinityGauntlet attacks showed how to brute-force fingerprints stored on an Android phone in about 40 minutes. The attacks are possible because biometrics, like passwords, do not have high entropy. But unlike passwords, brute-force attacks are much more damaging for biometrics, because one cannot easily change biometrics in case of compromise. In this work, we propose a novel provably secure Brute-Force Resistant Biometrics (BFRB) protocol for biometric-based authentication and key reconstruction that protects against brute-force attacks even when the server storing biometric-related data is compromised. Our protocol utilizes a verifiable partially oblivious pseudorandom function, an authenticated encryption scheme, a pseudorandom function, and a hash. We formally define security for a BFRB protocol and reduce the security of our protocol to the security of the building blocks. We implement the protocol and study its performance for the ND-0405 iris dataset.

We present an encrypted multi-map, a fundamental data structure underlying searchable encryption/structured encryption. Our protocol supports updates and is designed for applications demanding very strong data security. Not only it hides the information about queries and data, but also the query, access, and volume patterns. Our protocol utilizes a position-based ORAM and an encrypted dictionary. We provide two instantiations of the protocol, along with their operation-type-revealing variants, all using PathORAM but with different encrypted dictionary instantiations (AVL tree or BSkiplist). Their efficiency has been evaluated through both asymptotic and concrete complexity analysis, outperforming prior work while achieving the same level of strong security. We have implemented our instantiations and evaluated their performance on two real-world email databases (Enron and Lucene). We also discuss the strengths and limitations of our construction, including its resizability, and highlight that optimized solutions, even with heavy network utilization, may become practical as network speed improves.

This work presents a novel machine-checked tight security proof for $\mathrm{XMSS}$ — a stateful hash-based signature scheme that is (1) standardized in RFC 8391 and NIST SP 800-208, and (2) employed as a primary building block of $\mathrm{SPHINCS}^{+}$, one of the signature schemes recently selected for standardization as a result of NIST’s post-quantum competition. In 2020, Kudinov, Kiktenko, and Fedoro pointed out a flaw affecting the tight security proofs of $\mathrm{SPHINCS}^{+}$ and $\mathrm{XMSS}$. For the case of $\mathrm{SPHINCS}^{+}$, this flaw was fixed in a subsequent tight security proof by Hülsing and Kudinov. Unfortunately, employing the fix from this proof to construct an analogous tight security proof for XMSS would merely demonstrate security with respect to an insufficient notion. At the cost of modeling the message-hashing function as a random oracle, we complete the tight security proof for $\mathrm{XMSS}$ and formally verify it using the EasyCrypt proof assistant. As part of this endeavor, we formally verify the crucial step common to (the security proofs of) $\mathrm{SPHINCS}^{+}$ and $\mathrm{XMSS}$ that was found to be flawed before, thereby confirming that the core of the aforementioned security proof by Hülsing and Kudinov is correct. As this is the first work to formally verify proofs for hash-based signature schemes in EasyCrypt, we develop several novel libraries for the fundamental cryptographic concepts underlying such schemes — e.g., hash functions and digital signature schemes — establishing a common starting point for future formal verification efforts. These libraries will be particularly helpful in formally verifying proofs of other hash-based signature schemes such as $\mathrm{LMS}$ or $\mathrm{SPHINCS}^{+}$.

Fischlin's transform (CRYPTO 2005) is an alternative to the Fiat-Shamir transform that enables straight-line extraction when proving knowledge. In this work we focus on the problem of using the Fischlin transform to construct UC-secure zero-knowledge from Sigma protocols, since UC security -- that guarantees security under general concurrent composition -- requires straight-line (non-rewinding) simulators. We provide a slightly simplified transform that is much easier to understand, and present algorithmic and implementation optimizations that significantly improve the running time. It appears that the main obstacles to the use of Fischlin in practice is its computational cost and implementation complexity (with multiple parameters that need to be chosen). We provide clear guidelines and a simple methodology for choosing parameters, and show that with our optimizations the running-time is far lower than expected. For just one example, on a 2023 MacBook, the cost of proving the knowledge of discrete log with Fischlin is only 0.41ms (on a single core). This is 15 times slower than plain Fiat-Shamir on the same machine, which is a significant multiple but objectively not significant in many applications. We also extend the transform so that it can be applied to batch proofs, and show how this can be much more efficient than individually proving each statement. We hope that this paper will both encourage and help practitioners implement the Fischlin transform where relevant.

Sitting at the core of folding-based recursion, multi-instance accumulation still forces the recursive verifier to combine $\ell$ committed objects, incurring $\Theta(\ell)$ circuit-expensive commitment random linear combinations (CRCs). Here $\ell$ denotes the number of instances accumulated per step, and a CRC is an in-circuit random linear combination of commitments. Eliminating the linear-in-$\ell$ CRC overhead is the central challenge, and we address it with Quasar, reducing in-circuit CRCs from $\Theta(\ell)$ to $O(1)$ per step, while the unavoidable cost of reading and processing public inputs remains linear as usual. Realizing constant-commitment accumulation, Quasar's multi-cast reduction commits to a union polynomial and verifies a random partial evaluation, yielding a reduced instance with $O(1)$ commitments. Moreover, composing multi-cast with a standard $2$-to-$1$ folding reduction yields a multi-instance accumulation scheme whose verifier uses $O(\log \ell)$ field work and $O(1)$ CRCs per step. Across instantiations with suitable polynomial commitments, our instantiation supports linear-time accumulation provers, plausible post-quantum security, and parallelizable proving at each step. Not only does Quasar keep CRCs constant in $\ell$, it also yields a multi-instance incrementally verifiable computation with lower recursion overhead.

Homomorphic encryption (HE) offers strong privacy guarantees by enabling computation over encrypted data. However, the performance of tensor operations in HE is highly sensitive to how the plaintext data is packed into ciphertexts. Large tensor programs introduce numerous possible layout assignments, making it both challenging and tedious for users to manually write efficient HE programs. In this paper, we present Rotom, a compilation framework that autovectorizes tensor programs into optimized HE programs. Rotom systematically explores a wide range of layout assignments, applies state-of-the-art optimizations, and automatically generates an equivalent, efficient HE program. At its core, Rotom utilizes a novel, lightweight ApplyRoll layout conversion operator to easily modify the underlying data layouts and unlock new avenues for performance gains. Our evaluation demonstrates Rotom scalably compiles all tensor workloads in under 5 minutes, reduces rotations in hand-tuned protocols by up to 3×, and achieves up to 80× performance improvement over prior autovectorization systems.

In a secret sharing scheme for a monotone access structure $\mathcal{A}$, one can share a secret among a set of parties such that all subsets of parties authorized by $\mathcal{A}$ can reconstruct the secret while all other subsets learn nothing. However, what if an unauthorized subset of parties collude and offer their shares for sale? Specifically, suppose that the parties pool their shares to create a reconstruction box that reveals the secret upon receiving enough additional shares as input. To deter this behavior, Goyal et al. (CRYPTO'21) introduced the notion of traceable secret sharing (TSS), where it is possible to provably trace reconstruction boxes containing leaked secret shares back to their respective parties. Goyal et al. and subsequent work presented definitions and constructions of TSS for the threshold access structure. In this work, we revisit the notion of TSS. - We identify shortcomings in previous formulations of TSS and present new, strengthened definitions that are not achieved by known constructions. We show that it is easy to build reconstruction boxes for which the tracing guarantees of all previous works fail. - We extend the study of TSS beyond threshold to general access structures. Our new definitions are, in fact, necessary for this setting as natural adaptations of existing definitions become vacuous for general access structures. - We present new constructions of TSS that satisfy our definitions for all access structures captured by monotone circuits. One of our constructions relies solely on one-way functions while the other additionally relies on indistinguishability obfuscation.

Most polynomial commitment schemes have either superlinear prover time or superconstant argument size. Recently, Ganesh, Patranabis, and Singh introduced SamaritanPCS, and Eagen and Gabizon proposed Mercury. Both build on efficient univariate polynomial IOPs that lift univariate polynomial commitment schemes (PCSs) to the multilinear setting, enabling sum-check-based multilinear polynomial IOPs for prover-efficient zk-SNARKs with small communication. Since multilinear PCSs are fundamental building blocks of zk-SNARKs, they must be secure under minimal assumptions while remaining maximally efficient. However, SamaritanPCS and Mercury achieve knowledge soundness only in the joint random-oracle and algebraic-group model. We introduce Orca and Dolphin, optimized bivariate and multilinear PCSs, respectively. We prove that their interactive evaluation protocols have computational special soundness in the standard model, assuming that KZG satisfies binding and interpolation binding (both secure under ARSDH). Thus, they have knowledge soundness in the random oracle model. Both schemes can have a more efficient evaluation protocol that is knowledge sound in the joint random-oracle and algebraic-group model. Dolphin's evaluation phase is more efficient than either SamaritanPCS's or Mercury's.

A Chosen-Plaintext Attack (CPA) is a cryptographic analysis game for encryption, where an adversary queries an encryption oracle with plaintexts and observes the mapping to their ciphertexts. At an arbitrary time, it provides two challenge plaintexts but receives only one ciphertext, and finally guesses which of the two challenge plaintexts has been encrypted. Neural distinguishers, as a powerful representative of Artificial Intelligence (AI) methods, have been recently used in cryptographic analysis methods. However, they cannot directly be applied to perform CPA due to different input requirements and objectives. This work aims to address this gap. We provide the first rigorous and systematic formulation of CPA from a deep learning perspective. Specifically, we introduce NeuralCPA, a novel deep neural network-based method designed for the evaluation of block cipher CPA security as an initial effort for AI-based CPA analysis. We empirically validate its effectiveness across a diverse range of block ciphers, including SIMON, SPECK, LEA, HIGHT, XTEA, TEA, PRESENT, AES, and KATAN. Our experimental results confirm that NeuralCPA consistently achieves significant distinguishing advantages in round-reduced settings. Notably, our attack success rate ranges from 51% to 76.4%.

Password managers have become widely adopted and are commonly recommended to improve user security. However, current cloud-based solutions rely on the implicit assumption that password manager providers are fully trusted. This assumption is never questioned, as password managers are typically operated by their own designers, who are therefore judge and jury. Users are thus exposed to significant risks: a malicious provider could perform covert actions to access or alter credentials without being detected. Most password managers rely solely on the strength of a user-chosen master password. This design enables a covert adversary to mount large-scale offline attacks to crack weak master passwords. Even more concerning, some popular password managers do not encrypt credentials on users' devices, transmitting them in plaintext prior to server-side encryption, as is the case with Google default configuration. On the other hand, key-protected password managers such as KeePassXC offer stronger protection but lack native support for multi-device synchronization, limiting their adoption. Motivated by these observations, we define a comprehensive set of security properties that any cloud-based password manager should satisfy. We demonstrate that none of the widely deployed mainstream solutions fulfill these fundamental requirements. Nevertheless, we argue that it is feasible to design a password manager that is resilient to covert adversaries while supporting secure cross-device synchronization. To support our claims, we propose a provably secure design that meets all identified properties.

This self-contained and detailed tutorial covers RSA-based integer commitments and related protocols. It also presents a new, highly efficient setup protocol for sampling commitment parameters.

The past years have witnessed a considerable increase in research efforts on neural network-assisted profiled side-channel analysis (SCA). At the same time, studies have identified challenges, including closing the gap between machine learning (ML) classification metrics and side-channel attack evaluation. In fact, in NN-assisted SCA, the NN’s output distribution forms the basis for successful key recovery. In this respect, prior work has studied many aspects of integrating NNs into SCA, including model selection, training, and hyperparameter tuning. Nevertheless, a well-known fact has been largely overlooked in the SCA-related literature, namely NNs’ tendency to become over-confident, that is, assigning overly high probability to the correct class (the secret key in the sense of SCA). Temperature scaling is a powerful remedy for this behavior. From the perspective of deep learning, temperature scaling does not affect NN accuracy; however, its impact on secret-key recovery metrics, mainly guessing entropy, is worth investigating. This paper reintroduces temperature scaling into SCA and demonstrates that key recovery can become more effective. Importantly, temperature scaling can be integrated into SCA without re-tuning the network. In doing so, temperature can be treated as a metric to assess NN performance before launching the attack. In this regard, we study the impact of hyperparameter tuning, network variance, and capacity, and derive recommendations to prevent miscalibration and overconfidence.

Related-key differential neural distinguishers have recently attracted increasing attention in block-cipher cryptanalysis, yet their construction still relies heavily on cipher-specific manual design. In this paper, we study the systematic construction of related-key differential neural distinguishers for lightweight substitution–permutation network (SPN) block ciphers and propose a unified framework covering difference selection, dataset construction, network architecture, and training and evaluation. Within this framework, we develop a feature-enhancement method that exploits the invertibility of SPN components to derive representations more informative about the final-round internal state, and a sample-enhancement method that reuses each plaintext pair across related keys to derive multiple ciphertext-pair relations, thereby enriching each sample without increasing the plaintext budget. We validate the proposed framework on SKINNY-64/64 and PRESENT-64/80. Experimental results demonstrate that the proposed method can effectively construct multi-round related-key differential neural distinguishers, with accuracy improving consistently as the number of plaintext pairs per sample increases. In particular, for SKINNY-64/64, the single-pair setting achieves classification accuracies of 100.0%, 68.2%, and 59.3% for 7, 8, and 9 rounds, respectively, providing, to the best of our knowledge, the first experimental results on related-key differential neural distinguishers for this cipher. For PRESENT-64/80, under the four-pair setting, the proposed method achieves competitive distinguishing performance up to 9 rounds, with accuracies of 95.6%, 72.0%, and 53.7% for 7, 8, and 9 rounds, respectively.

We construct a lattice-based ciphertext-policy attribute-based encryption (CP-ABE) scheme for $\mathsf{NC}^1$ access policies with constant-size ciphertexts. Let $\lambda$ be the security parameter. For an $\mathsf{NC}^1$ circuit of depth $d$ and size $s$ on $\ell$-bit inputs, our scheme has the public-key and ciphertext sizes $O(1)$ (independent of $d$), and secret-key size $O(\ell)$, where the $O(\cdot)$ hides $\operatorname{poly}(\lambda)$ factors. As an application, we obtain a broadcast encryption scheme for $N$ users with ciphertext size $\operatorname{poly}(\lambda)$ independent of $\log N$ and key sizes $\operatorname{poly}(\lambda,\log N)$. Our construction is selectively secure in the standard model under the $\operatorname{poly}(\lambda)$-succinct LWE assumption introduced by Wee (CRYPTO 2024).

Understanding the complexity of Byzantine agreement (BA) is a fundamental problem in distributed computing and cryptography. Existing round- or communication lower bounds either restrict the class of protocols they apply to in terms of communication, setup assumptions, or determinism. Another class of lower bounds holds only with respect to a very powerful (arguably unrealistic) adaptive adversary that can delete undelivered messages sent by a newly corrupted party while it was still honest. On the other hand, many popular BA protocols including the consensus protocol underlying the Algorand cryptocurrency assume only a standard adaptive adversary which cannot perform after-the-fact message removals. In this work, we aim to further narrow the gap between existing upper and lower bounds. We first revisit existing communication lower bounds of Abraham et al. (PODC 2019) and Blum et al. (TCC 2020) which show that, under certain conditions, $\Omega(t^2)$ messages are necessary in expectation for randomized BA protocols with security against $t$ adaptive corruptions. We give two new lower bounds on the communication complexity of randomized BA protocols that hold against even a standard adaptive adversary, for previously unexplored settings of practical interest. Our bounds assume a complete network of authenticated communication channels. Our first bound improves over Abraham et al. when the setup is limited to a common reference string (CRS), and the second one improves the bit complexity of Blum et al since in the authenticated setting, i.e., we allow idealized signatures. As a technical contribution, we present a new formal model for protocols using idealized signatures, which may be of independent interest. We then turn our attention to the round complexity of randomized BA protocols in which only a subset of parties may speak. We show that such protocols must either rely on erasures or determine whether or not to first speak in the protocol and decide in dependence the parties' inputs. We discuss in detail how both of these design paradigms have been used in prior work and how they lead to efficiency and design-related issues for practical BA protocols.

Traceable Receipt-free Encryption (TREnc) has recently been introduced by Devillez, Pereira and Peters (Asiacrypt’22) as a verifiable public-key encryption primitive allowing to randomize ciphertexts in order to remove any subliminal information up to a public trace which prevents the malleability of the underlying plaintexts. This unique feature generically enables the construction of voting systems by allowing voters to encrypt their votes, tracing whether a published ballot takes their choices into account, and preventing them from proving how they voted. While being a very promising primitive, the few existing TREnc mechanisms solely rely on discrete-logarithm related assumptions making them vulnerable to the well-known harvest now, decrypt later attack in the wait of quantum computers. In this article, we address this limitation by building the first TREnc which can be safely used today until the advent of quantum adversaries. More precisely, based on the observation that security must hold at the time the primitive is used while only privacy should withstand in the post-quantum era, our solution relies on a mix of pre-quantum and post-quantum cryptography. As a first contribution, we generalize the original TREnc primitive that is too restrictive to be easily compatible with built-in lattice-based semantically-secure encryption. Our more flexible model keeps all the ingredients generically implying receipt-free voting. Next, we design our construction with the following essential proper- ties for trustworthy elections: (i) it is provably-secure in the standard model; (ii) it relies on standard assumptions, namely Ring Learning With Errors (RLWE) coupled with pairing-based statistical zero-knowledge simulation-sound SXDH-based proofs; and (iii) it further enjoys a public-coin common reference string removing the need of a trusted setup.

We specify OCH, the first authenticated encryption with associated data scheme built to provide 128-bit multi-user AE security, 128-bit context commitment security, and 256-bit nonces with optional nonce privacy. It therefore addresses pressing limitations of currently widely-deployed schemes. We construct and formally analyze the security of OCH in a modular fashion, with transforms that are of broader applicability. On Intel Raptor Lake CPUs, OCH using the Areion permutation family has a peak encryption speed of 0.62 cycles per byte (cpb), not far off from AES128-GCM (0.38cpb) and outperforming both ChaCha20/Poly1305 (1.63cpb) and TurboSHAKE128-Wrap (3.52cpb).

In the modern, globalized supply chain for application specific integrated circuits (ASICs), reverse engineering (RE) techniques can be employed for malicious and benign reasons. This survey defines the specific problem of logical RE from a hardware security perspective, examines the earliest RE-adjacent techniques, organizes contemporary RE works by both objective and methodology, and summarizes publication trends and the evolution of logical RE over the years. We review existing techniques, tracing their evolution from manual evaluation and structural analysis to graph theory and machine learning-based solutions. In addition, the survey identifies common trends and evaluation practices, discussing the strengths and drawbacks of the current literature. We also present a set of unique unaddressed problems, highlighting areas that have not been sufficiently explored as well as completely novel problems in ASIC RE. In conclusion, our findings provide a valuable foundation for researchers interested in RE and the future of the field.

Username & password is the most common authentication method in Web2 because of its high usability and efficient protection against brute-force attacks by applying rate limits on the server. In contrast, Web3 wallets cannot securely support password-derived keys. Passwords typically have low entropy, and because blockchain environments are public and impose no rate limits on brute-force attempts, attackers can repeatedly test guesses offline until the private key is recovered. In this work, we present a novel password-based blockchain wallet that enables secure management of private keys (of any blockchain type) within a privacy-preserving smart contract platform (PPP). To store the keys, we adapt the OPAQUE protocol to fit the decentralized environment of blockchains and leverage the properties of TEE within PPP. Our design consists of the client, relay, and smart contract deployed at PPP. To this end, we propose the user enrollment protocol and private key retrieval protocol that require knowledge of the username and password and apply blockchain-enforced rate limits on guessing attempts. Our implementation is based on the Oasis Sapphire confidential EVM as an instance of PPP. Our system implements OPAQUE’s Oblivious Pseudorandom Function (OPRF) inside a smart contract, allowing the contract to act as the protocol’s server while keeping the long-term OPRF key protected within the enclave. During authentication, the client performs a blinded OPRF interaction so that neither the password nor its derivatives are revealed to the relay, blockchain, or the public. Experiments show that a single authentication attempt requires approximately 500k and 300k gas for 2048-bit and 1024-bit numbers within finite-field DLP, respectively, while one-time registration costs approximately 270k gas.

Differential privacy (DP) is one of the most efficient tools for protecting the privacy of individual data holders under computation. This property guarantees that the computation outputs for every pair of adjacent input sets are statistically indistinguishable with respect to a given parameter ε, which is independent of the likelihood that specific inputs occur or not. While the distribution of input sets is generally unknown, in some use cases (approximate) information about it might be available. If the latter is the case, two adjacent inputs of one individual are sometimes already obfuscated by other inputs and the computation itself (i.e., without any additional noise). For example, if the sum of n independent and identically distributed uniformly random bits outputs approximately n/2, both values for the first bit remain (almost) equally likely for large n. Based on this observation, we present a new DP mechanism that uses an estimate of the input distribution to reduce the noise addition (compared to standard DP) and hence improves the accuracy of the output. We first explore this idea in the central model, where a single central party collects all data. Then, we provide a new technique (possibly of independent interest) that allows multiple entities to jointly generate reduced noise, using the property of infinite divisibility. This allows each party to individually add noise to their respective inputs, e.g., in Federated Analytics applications. We apply our theoretical results, both for the single and multi-party setups, to perform data analysis over human resources data from different subsidiaries within a corporate group. Our benchmarks show that our new DP mechanism provides more accurate outputs while retaining the same privacy level as state-of-the-art DP approaches using the geometric mechanism.

While the Weil pairing is geometric, the Tate pairing is arithmetic: its value depends on the base field considered. Nevertheless, the étale topology allows to interpret the Galois action in a geometric manner. In this paper, we discuss this point of view for the Tate pairing: its natural geometric interpretation is that it gives étale $\mu_n$-torsors. While well known to experts, this interpretation is perhaps less known in the cryptographic community. As an application, we explain how to use the Tate pairing to study the fibers of an isogeny, and we prove a conjecture by Castryck and Decru on multiradical isogenies.

We extend the usual ideal action on oriented elliptic curves to a (Hermitian) module action on oriented (polarised) abelian varieties. Oriented abelian varieties are naturally enriched in $R$-modules, and our module action comes from the canonical power object construction on categories enriched in a closed symmetric monoidal category. In particular our action is canonical and gives a fully fledged symmetric monoidal action. Furthermore, we give algorithms to compute this action in practice, generalising the usual algorithms in rank~$1$. The action allows us to unify in the same framework, on the one hand isogeny based cryptography based on ordinary or oriented elliptic curves, and on the other hand the one based on supersingular elliptic curves defined over $\mathbb{F}_{p^2}$. In particular, from our point of view, supersingular elliptic curves over $\mathbb{F}_p$ are given by a rank~$1$ module action, while (the Weil restriction) of those defined over $\mathbb{F}_{p^2}$ are given by a rank~$2$ module action. As a consequence, rank~$2$ module action inversion is at least as hard as the supersingular isogeny path problem. We thus propose to use Hermitian modules as an avatar of a cryptographic symmetric monoidal action framework. This generalizes the more standard cryptographic group action framework, and still allows for a NIKE (Non Interactive Key Exchange). The main advantage of our action is that, presumably, Kuperberg's algorithm does not apply. Compared to CSIDH, this allows for more compact keys and much better scaling properties. In practice, we propose the key exchange scheme $\otimes$-MIKE (Tensor Module Isogeny Key Exchange). Alice and Bob start from a supersingular elliptic curve $E_0/\mathbb{F}_p$ and both compute a $2^n$-isogeny over $\mathbb{F}_{p^2}$. They each send the $j$-invariant of their curve. Crucially, unlike SIDH, no torsion information at all is required. Their common secret, given by the module action, is then a dimension~$4$ principally polarised abelian variety. We obtain a very compact post-quantum NIKE: only 64B for NIST level~$1$ security.

Abstract. We present a novel side-channel attack on first-order masked implementations of Crystals-Kyber. It deploys a new distinguisher in the context of post-quantum cryptography. It relies on combining the in formation from several instances of the same distinguisher via multiple ciphertexts decryption requests. The attack has been performed on simu lation and illustrated on the masked implementation of Bronchain et al.. This attack is instantiated in a very noisy environment (Signal-to-Noise Ratio (SNR) of 0.67) and provides a success rate of 95% with 75000 traces for full secret key recovery.

Motivated by the mismatch between floating-point arithmetic, which is intrinsically approximate, and verifiable computing protocols for exact computations, we develop a generalization of the sum-check protocol. Our generalization proves claims of the form $\sum_{x \in \{0,1\}^v} g(x) \approx H$, where $g$ is a low-degree $v$-variate polynomial over an integral domain $\mathbb{U}$. The verifier performs its check in each round of the protocol using a tunable error parameter $\delta$. If $\Delta$ is the error in the prover's initial claim, then the soundness error of our protocols degrades gracefully with $\delta/\Delta$. In other words, if the initial error $\Delta$ is large relative to $\delta$, then the soundness error is small, meaning the verifier is very likely to reject. Unlike the classical sum-check protocol, which is fundamentally algebraic, our generalization exploits the metric structure of low-degree polynomials. The protocol can be instantiated over various domains, but is most natural over the complex numbers, where the analysis draws on the behavior of polynomials over the unit circle. We also analyze the protocol under the Fiat-Shamir transform, revealing a new intermediate security phenomenon that appears intrinsic to approximation. Prior work on verifiable computing for numerical tasks typically verifies that a prover exactly executed a computation that only approximates the desired function. In contrast, our protocols treat approximation as a first-class citizen: the verifier's checks are relaxed to accept prover messages that are only approximately consistent with the claimed result. This establishes the first black-box feasibility result for approximate arithmetic proof systems: the protocol compiler is independent of how arithmetic operations are implemented, requiring only that they satisfy error bounds. This opens a path to verifying approximate computations while sidestepping much of the prover overhead imposed by existing techniques that require encoding real-valued data into finite field arithmetic.

The decentralisation of autonomous Unmanned Aircraft Systems (UAS) introduces significant challenges for establishing secure communication and consensus in contested, resource-constrained environments. This research addresses these challenges by conducting a comprehensive performance evaluation of two cryptographic technologies: Messaging Layer Security (MLS) for group key exchange, and threshold signatures (FROST and BLS) for decentralised consensus. Seven leading open-source libraries were methodically assessed through a series of static, network-simulated, and novel bulk-signing benchmarks to measure their computational efficiency and practical resilience. This paper confirms that MLS is a viable solution, capable of supporting the group sizes and throughput requirements of a UAS swarm. It corroborates prior work by identifying the Cisco MLSpp library as unsuitable for dynamic environments due to poorly scaling group management functions, while demonstrating that OpenMLS is a highly performant and scalable alternative. Furthermore, the findings show that operating MLS in a 'Key Management' mode offers a dramatic increase in performance and resilience, a critical trade-off for UAS operations. For consensus, the benchmarks reveal a range of compromises for developers to consider, while identifying the Zcash FROST implementation as the most effective all-around performer for sustained, high-volume use cases due to its balance of security features and efficient verification.

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 the 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 the new HHE-enabling schemes using ATXmega128D4-AU microcontroller. Finally, we extend Sasta-DFA to Authenticated Transciphering protocols under a weaker threat model that removes any functional dependency.

Quantum computers can break or weaken classical cryptography using Shor’s and Grover’s algorithms. This threat drives the development of post-quantum cryptography (PQC) algorithms, such as the Classic McEliece (CM) algorithm, which resists quantum attacks by relying on hard problems in coding theory. However, the complex computation and large key size make it challenging to implement CM in an efficient way in terms of computational performance. This research is the first to thoroughly explore and implement RISC-V Vector Extensions (RVV) for the acceleration of the CM key generation process. First, an evaluation is done of auto-vectorized and manually vectorized implementations of CM using the RISC-V Vector Extension Version 1.0 (RVV1.0), based on multiple vector register configurations. Further, several new custom RVV instructions are proposed to speed up the implementation even more. The presented work gives insight into the practical implementation capabilities of RVV for the speed-up of CM key generation on an FPGA.

In the recent preprint [GMS26], Grigoriev, Monico and Shpilrain proposed a digital signature protocol based on matrices over the tropical integer semiring. we show that the scheme can be completely broken. We present a chosen‑hash forgery, a malleability attack that breaks strong unforgeability, and an SMT‑based key recovery attack demonstrating that a single valid signature together with the public key suffices to recover a full private key in within one second for the recommended parameters. Our attacks exploit algebraic properties of the signing equations rather than the claimed NP‑hard problem. Independent work by Sferlazza concurrently identified related vulnerabilities.

Quantum fire is a distribution of quantum states that can be efficiently cloned, but cannot be efficiently converted into a classical string. First considered by Nehoran and Zhandry (ITCS'24) and later formalized by Bostanci, Nehoran, Zhandry (STOC'25), quantum fire has strong applications and implications in cryptography, along with important connections to physics and complexity. However, constructing and proving the security of quantum fire so far has been elusive. Nehoran and Zhandry showed how to construct quantum fire relative to an inefficient quantum oracle (which cannot be instantiated even heuristically). Later, Bostanci, Nehoran, Zhandry gave a candidate construction based on group actions, however, even in the classical oracle model they could only conjecture the security of their scheme, and were not able to give a security proof or argue security. In this work, for the first time, we give a construction of public-key quantum fire relative to a classical oracle and prove its security unconditionally. Going further, we introduce two stronger notions that generalize quantum fire, and we give secure constructions for these notions. *** We introduce a notion called quantum key-fire where the clonable fire states serve as keys: They can be used to evaluate a functionality (such as a signing or decryption key), and for security we require unbounded leakage-resilience, which means that given the fire state, the key cannot be efficiently converted into a classical string. *** We consider the notion of interactive (i.e. LOCC) security for quantum (key-)fire. In this setting, instead of trying to convert the state or key into a classical string; the adversary, given the flame state, attempts to transfer it to another adversary interactively over a classical channel. We give a construction of quantum key-fire relative to a classical oracle and unconditionally prove that it satisfies interactive security for any unlearnable functionality. As a result, we also obtain the first classical oracle separations between various notions in physics and cryptography: *** A separation in the computational universe between two fundamental principles of quantum mechanics: No-cloning and no-teleportation, which are equivalent in the information-theoretic setting. *** A separation between copy-protection security (Aaronson, CCC'09) and unbounded/LOCC leakage-resilience security (Cakan, Goyal, Liu-Zhang, Ribeiro, TCC'24). *** A separation between computational no-cloning security and computational no-learning security, two notions introduced recently by Fefferman, Ghosh, Sinha, Yuen (ITCS'26). In all our constructions, the oracles can be implemented efficiently using one-way functions. Thus, our schemes can be heuristically instantiated in the plain model using one-way functions and indistinguishability obfuscation, which gives us the first constructions in the plain model with concrete evidence for their security.

Multi-scalar multiplication (MSM) is a central kernel in cryptographic systems, which evaluates large linear combinations of elliptic-curve points. Practical MSMs couple millions of terms with hundreds-of-bit modular arithmetic, while Pippenger’s bucket flow introduces irregular memory updates that can severely degrade utilization under deep pipelines. In this paper, we present UniMSM, an efficient and flexible hardware accelerator for MSM across practical problem sizes and diverse curve parameters. First, we design a pipelined point adder based on the extended Jacobian coordinate system and employ a time-multiplexed datapath to reduce modular multiplier cost while sustaining high throughput. Second, we introduce a conflict-aware scheduling scheme to address bucket-update conflicts and preserve utilization under irregular accesses. Third, we develop a hardware-friendly variant of the Pippenger algorithm to reduce intermediate storage overhead and serial dependencies in aggregation. Compared with prior FPGA accelerators, UniMSM achieves up to 2.12$\times$ improvement in area-time product. Furthermore, UniMSM in ASIC achieves up to a 3.85$\times$ improvement in ATP compared to the SOTA accelerator.

Ransomware remains a persistent cybersecurity threat difficult to detect due to high-dimensional network traffic and sophisticated obfuscation techniques. Existing feature selection methods often struggle with redundancy, noise, and the curse of dimensionality, leading to poor generalisation and limited interpretability in ransomware detection. To address these challenges, we propose BioSparse-MCP, a hybrid feature selection framework that integrates gradient-based optimisation with the Minimax Concave Penalty (MCP) to enforce sparsity, alongside a Rotated Circular Partitioning (RCP) strategy to improve the spatial organisation of selected features. This design reduces redundancy, enhances discriminative power, and provides rotation-aware representations that overcome the limitations of conventional dimensionality reduction. The framework further incorporates a Quantum Feature Mapping (QFM)-inspired geometric transformation, in which features are projected onto a spherical space, rotated, and partitioned into angular sectors, while preserving linear computational complexity. All RCP and QFM operations are classically simulated, ensuring compatibility with conventional machine learning pipelines and real-time deployment without specialised hardware. Implemented in Python using standard numerical libraries, BioSparse-MCP was evaluated on 149,043 network traffic instances with an ensemble of KNN and LSTM models. The approach achieved high detection accuracy with a low False Positive Rate (0.25%). Feature attribution analysis highlights cryptocurrency addresses, threat signatures, and IP-level features as key contributors. These results demonstrate that combining sparse optimisation with quantum-inspired geometric encoding provides an efficient and interpretable solution for ransomware detection in high-dimensional network environments.

Nitaj and Seck recently published an RSA variant (MJAGA 2024) based on the cubic Pell equation $\mathcal{P}_c(N): u^3+cv^3+c^2w^3-3cuvw= 1$ over $\mathbb{Z}/N\mathbb{Z}$ when $N=p^rq^s$. In their cryptosystem, the public exponent $e$ and the private exponent $d$ are related to the key equation $d\equiv e^{-1}\pmod{p^{2(r-1)}q^{2(s-1)}(p-1)^2(q-1)^2}$. In AfricaCrypt 2025, Rahmani and Nitaj published a lattice attack on their scheme in the particular case of $r=s=1$ by exploiting the key equation $ed - (p-1)^2(q-1)^2 k = 1$. In this paper, we present a new generalized partial exposure lattice attack on the scheme of Nitaj and Seck by examining the key equation $eu_0 - (p-1)^2(q-1)^2 v_0 = w_0$ when some bits of $p$ or $q$ are known.

We present the first Interactive Oracle Proof of Proximity (IOPP) for linear-time encodable codes that achieves $\lambda$-bit security with linear prover time and optimal $O(\lambda)$ query complexity. This implies (via standard techniques) the first IOP for NP with $O(n)$ prover time and $O(\lambda)$ query complexity, and hence also the first SNARK for NP in the random oracle model with linear prover time and $O(\lambda^2 \log n)$ proof size. The technical core of our result is a novel IOPP for tensor codes. Our tensor IOPP leverages error correction in a novel way to reduce checking proximity of a purported codeword to the tensor code to checking the proximity of $\Theta(\lambda)$-many of its columns to the column code. Our key insight is that it in fact suffices to just prove that a constant fraction of these new proximity claims hold (as opposed to all of them). We devise a new lossy batching protocol that provides the foregoing guarantee with just $O(\lambda)$ query complexity. By combining this tensor IOPP with prior "codeswitching" reductions, we obtain IOPPs for a large class of linear-time encodable codes. We complement our IOPP construction with a lower bound that shows that, when proving proximity to constant-rate codes, one cannot construct IOPPs with query complexity better than $O(\lambda)$. This establishes the optimality of our IOPP's query complexity.

Fully Homomorphic Encryption (FHE) allows users to offload large computations to servers without revealing the underlying data. Due to this unique feature, it is applicable to a variety of domains, including privacy-preserving Machine Learning. However, all FHE schemes have two problems- slow encryption/decryption and substantial ciphertext expansion. Thus, despite its significant potential, the practical implementation of FHE faces considerable challenges due to massive computation and communication overhead. In this work we address this gap, and propose a novel \tonetwo approach to optimize client-side homomorphic encryption, leveraging bootstrapping. This technique minimizes ciphertext expansion and reduces the communication overhead on the server as well as the client. We also eliminate the need for encoding and decoding by the client, thereby omitting the floating-point arithmetic requirement for FHE over approximate numbers. The elegance of this technique lies in its ability to utilize the built-in FHE routines and inherently maintain security and precision guarantees. The proposed technique reduces the enc/decryption computation and communication requirements by up to $97\%$. We employ the proposed techniques to develop a framework for FHE client operations that is compatible with both software and hardware platforms. We conduct a comprehensive design analysis and FPGA prototyping, present ASIC synthesis results, and provide microcontroller performance evaluations. The efficient architecture design methodology demonstrates up to $76\times$ speedup compared to prior works on the same platform.

Single Sign-On (SSO) protocols allow an identity provider to authenticate users and report the outcome by issuing identity attestations. Recent attacks show that breaching the identity provider infrastructure enables adversaries to issue arbitrary identity attestations and impersonate users. Survivable SSO protocols limit the risks of similar intrusions, but they have only been defined for password-based authentication, inheriting their limitations against powerful attacks such as credential phishing. While phishing-resistant passwordless authentication protocols have been standardized, they are not designed to guarantee intrusion tolerance. We initiate the research for Survivable Passwordless SSO (SPS) and propose a modular approach which includes the novel definition of Survivable Passwordless Challenge-response (SPC) protocols for authentication as a sub-routine of SSO. We give the first frameworks and game-based security definitions both for SPC and SPS which capture both novel attack classes, such as session injection attacks in a decentralized setting, and existing but not yet formalized attack classes, such as detection of cloned authenticators. The design of the models includes novel strategies to capture proactive security in survivable protocols within security definitions and to compose authentication and SSO through a modular approach. Our strategies and models may also be applied with minor modifications to non-survivable protocols, possibly providing a novel approach to assess the security of existing SSO protocols.

Additive randomized encodings (ARE), introduced by Halevi, Ishai, Kushilevitz, and Rabin (CRYPTO 2023), reduce the computation of a k-party function $f (x_1, . . . , x_k )$ to locally computing encodings $\hat{x}_i$ of each input xi and then adding them together over some Abelian group into an output encoding $\hat{y} = ∑ \hat{x}_i$, which reveals nothing but the result. In robust ARE (RARE) the sum of any subset of $\hat{x}_i$, reveals only the residual function obtained by restricting the corresponding inputs. The appeal of (R)ARE comes from the simplicity of the online part of the computation involving only addition, which yields for instance non-interactive multi-party computation in the shuffle model where messages from different parties are anonymously shuffled. Halevi, Ishai, Kushilevitz, and Rabin constructed ARE from standard assumptions and RARE in the ideal obfuscation model, leaving open the question of whether RARE can be constructed in the plain model. We construct RARE in the plain model from indistinguishability obfuscation, which is necessary, and a new primitive that we call pseudo-non-linear codes. We provide two constructions of this primitive assuming either Learning with Errors or Decision Diffie Hellman. A bonus feature of our construction is that it is online succinct. Specifically, encodings $\hat{x}_i$ can be decomposed to offline parts $\hat{z}_i$ that can be sent directly to the evaluator and short online parts $\hat{g}_i$ that are added together.

We present a novel linkable ring signature scheme that possesses unconditional anonymity together with a voting protocol that utilizes it to achieve coercion resistance and everlasting privacy. In our system, all voters create private credentials and register their public counterparts. To vote, they create a ring (anonymity set) consisting of public credentials together with a proof of knowledge of their secret credential by using our novel signature. Its unconditional anonymity prevents an attacker, no matter how powerful, from deducing the identity of the voter, thus attaining everlasting privacy. Additionally, our protocol provides coercion resistance in the JCJ framework; when an adversary tries to coerce a voter, the attack can be evaded by creating a signature with a fake but indistinguishable credential. During a moment of privacy, the voter will cast their real vote. Our scheme also provides verifiability and ballot secrecy.

We present a privacy protocol implemented on Starknet that enables confidential transactions while maintaining regulatory compliance. Transfers hide the sender, receiver, and amount from external observers, with validity enforced by zero-knowledge proofs generated on the client side using the Stwo STARK prover. The protocol introduces three key innovations: (1) an efficient note discovery mechanism, (2) a practical compliance framework that enables an auditing entity to selectively unshield transactions upon legitimate regulatory request, and (3) anonymous integration with existing Starknet DeFi contracts. The system supports multiple token types in a single pool and leverages Starknet's native account abstraction for transaction authorization. All proof logic and contract code are written in Cairo, providing a unified codebase that simplifies auditing and development.

Data regulations grant users the right to be forgotten, empowering them to control if and when their data is used in applications such as machine learning training. Machine unlearning offers a promising mechanism to enforce this right by enabling the removal of specific training data from models. Existing machine unlearning approaches, however, assume an honest server that correctly executes all unlearning requests. In practice, this assumption is too strong: nothing prevents a server from falsely claiming to have performed unlearning while secretly retaining the original model or continuing to use the data for training. Such behaviours remain possible even when unlearning requests are verifiable---for example, via zero-knowledge proofs---because the server may still keep copies of the data or model. In this work, we argue that a security model for machine unlearning should capture data confidentiality throughout the lifecycle of a model, including training, inference, and unlearning. We introduce such a formalism and then present the first machine learning framework that provides cryptographic guarantees that unlearning requests are properly executed and that users' data is forgotten. We implement our framework using fully-homomorphic encryption (FHE) and secure multi-party computation (MPC), within a distributed setting where training, unlearning and inference requests are handled by a group of servers. Our constructions are secure in the honest-but-curious model if at least one of the servers is honest, and can be lifted against actively malicious servers following standard techniques. We also show, via a proof-of-concept implementation, that such a system does not add a significant overhead on top of FHE-based training.

Achieving proactive security in perfectly-secure Multi-Party Computation (MPC) with guaranteed output delivery is a significant challenge, primarily because traditional protocols require all participants to be continuously online, rendering them impractical for many applications. The recently proposed layered MPC model~\cite{C:DDGIKK23} addresses this by allowing parties to be offline for extended periods. However, existing protocols for this model incur substantial overhead compared to their counterparts in the standard static setting. This work introduces a unified framework and essential building blocks for constructing protocols in the layered model, instantiable with both Shamir and CNF secret sharing. Using this framework, we develop highly efficient protocols for Verifiable Secret Sharing (VSS) and secure multiplication for proactive security. Applying our framework, we construct layered MPC protocols that drastically reduce the communication complexity and the number of layers required to evaluate an arithmetic circuit of depth $D$. Specifically, our Shamir-based MPC achieves $O(n^6)$ per-gate communication with a total layer depth of $D+13$, representing a significant improvement over the $O(n^9)$ complexity and $10D+8$ depth of~\cite{C:DDGIKK23}.

Federated Learning (FL) has emerged as a prominent paradigm for collaborative machine learning that enables model training without exposing private data through data decentralisation. Despite these advantages, FL systems remain vulnerable to significant security challenges affecting both privacy and robustness. This paper examines vulnerabilities in FL with a particular focus on model robustness, identifying critical gaps in existing defences against adaptive adversaries that alter their attack strategies after disconnection and subsequently rejoin the system. To the best of our knowledge, prior surveys have not explicitly addressed adaptive adversaries, motivating the focus of this work. We make five contributions: (1) a comprehensive overview of FL systems and their fundamental components, (2) a systematic review of vulnerabilities affecting FL, (3) an analysis of baseline attack vectors alongside state-of-the-art attack and defence mechanisms, (4) the introduction of a novel baseline attack based on Reconnecting Malicious Clients (RMCs), and (5) identification of future research directions for mitigating adaptive attacks. Experimental results demonstrate that widely used secure aggregation rules, including Krum and Trimmed Mean (commonly used as a baseline for other solutions to compare against), are insufficient against such attacks, and existing improvements to these methods fail to address this limitation. These findings highlight the need to reconsider FL security paradigms with explicit consideration of adaptive adversaries.

In an $(\varepsilon_s,\varepsilon_z)$-weak non-interactive zero knowledge (NIZK), the soundness error is at most $\varepsilon_s$ and the zero-knowledge error is at most $\varepsilon_z$. Goyal, Jain, and Sahai (CRYPTO 2019) stated that if $\varepsilon_s+\varepsilon_z < 1$ for some constants $\varepsilon_s,\varepsilon_z$, then $(\varepsilon_s,\varepsilon_z)$-weak NIZK can be turned into fully-secure NIZK, assuming sub-exponentially-secure public-key encryption. However, they have since discovered a gap in their proof. We revisit the problem of NIZK amplification: –We amplify NIZK arguments assuming only polynomially-secure public-key encryption, for any constants $\varepsilon_s+\varepsilon_z < 1$. –We amplify NIZK proofs assuming only one-way functions, for any constants $\varepsilon_s+\varepsilon_z < 1$. –When the soundness error $\varepsilon_s$ is negligible to begin with, we can also amplify NIZK arguments assuming only one-way functions. Our results take a different route than that of Goyal, Jain, and Sahai. They are based on the hidden-bits paradigm, and can be viewed as a reduction from NIZK amplification to the better understood problem of pseudorandomness amplification.

Group signatures (GS) are a well-known cryptographic primitive that provide both anonymity and traceability. Several implication results have been established, mainly focusing on different security levels of anonymity. For example, fully anonymous GS implies public-key encryption (PKE), and selfless anonymous GS can be constructed from one-way functions and non-interactive zero-knowledge proofs, among others. In this paper, we explore a winning condition for full traceability: an adversary must produce a valid group signature whose opening reveals an uncorrupted user. We present a generic construction of GS that is secure in the Bellare-Micciancio-Warinschi (BMW) model, except for the above condition, based solely on PKE. We emphasize that the proposed construction is highly artificial and practically meaningless because the verification algorithm always outputs 1 regardless of the input. This result suggests that the winning condition is essential for full traceability, namely that an uncorrupted user must exist.

Privacy-Preserving Federated Learning (PPFL) emphasizes the security and privacy of contributors' data in scenarios such as healthcare, smart grids, and the Internet of Things. However, ensuring the security and privacy throughout PPFL can be challenging, given the complexities of maintaining relationships with many users across multiple epochs. Additionally, under a threat model in which the aggregating server and corrupted users are colluding adversaries, honest users' inputs and output data must be protected at all stages. Two common tools for enforcing privacy in federated learning are Private Stream Aggregation (PSA) and Trusted Execution Environments (TEE). However, PSA-only approaches still expose the raw aggregate to the server (and thus to colluding parties). TEE-only aggregation typically incurs non-negligible per-client per-epoch overhead at scale because the TEE must handle per-client communication and maintain per-client state/key material. This paper presents SCALE-FL, a novel solution for PPFL that maintains security while achieving near-plaintext performance using a state-of-the-art PSA protocol to collect user information and a TEE to hide information about the raw aggregate. By using a PSA protocol for aggregation, we can maintain the privacy of information on the untrusted server without requiring per-user key storage or use by the TEE. Then, the aggregate is securely processed by the TEE in plaintext, without the heavy encryption required on an untrusted server. Finally, we ensure the security of user inputs in the federated learning output by using Differential Privacy (DP). The additional overhead introduced by SCALE-FL is 1% of the overhead of the plain FL executions.

Compression has been a fundamental problem in computer science for decades. Simply put, we want to represent a low-entropy vector $v$ of size $n$ with less than $n$ elements so that $v$ can be reconstructed (decompressed) from the shorter representation. Since compressed vectors require less storage and less communication, compression algorithms are part of almost every digital system. When the vector is encrypted with fully homomorphic encryption (FHE) the problem becomes significantly harder. Some research (e.g., [TCHES'19, CCS'21, EuroCrypt'23 ,USENIX'24]) have considered the problem of compressing an encrypted vector but they all assumed the decompression step happens in cleartext. This is a significant restriction. For example, any system with an untrusted agent that needs to receive data and analyze it cannot use existing compression algorithms. In this paper, we give the first (to the best of our knowledge) non-trivial compression-decompression algorithms that are both FHE-friendly. Our algorithms use the copy-and-recurse technique together with the known duality between compression and error-correcting codes. Our experiments show that our decompression algorithm is faster than the folklore decompression algorithm. This is useful in systems with an agent-in-the-middle that is bounded by communication and by computation.

Hybrid cryptographic schemes combine multiple primitives to provide resilience against diverse threats, particularly in the post-quantum era where classical algorithms face potential quantum attacks. However, existing hybrid approaches rely on predefined, fixed pairings of specific cryptographic algorithms, limiting their adaptability to evolving security requirements and heterogeneous deployment environments. This paper presents a generalized framework for the hybridization of cryptographic primitives that enables dynamic, user-driven composition of encryption schemes and digital signatures. Our approach leverages all-or-nothing transformations (AONTs) to construct hybrid schemes where an adversary must break all constituent primitives simultaneously to compromise the system. We formally prove that if at least one component scheme remains secure (IND-CPA for encryption, EUF-CMA for signatures), the entire hybrid construction achieves security equivalent to its strongest component. Unlike conventional approaches that prescribe specific algorithm combinations, our framework allows flexible selection and integration of classical, post-quantum, or mixed cryptographic primitives based on specific security requirements, computational constraints, and threat models. Our generalized hybridization methodology naturally extends to key encapsulation mechanisms and other cryptographic primitives, providing a foundation for building future adaptive cryptographic systems that remain secure even as individual components are compromised over time. This addresses a critical gap in current cryptographic practices and will provide users a methodology to construct flexible, robust security architectures for the post-quantum era.

Lattice-based cryptography (LBC) has emerged as one of the most promising fields supporting post-quantum cryptography (PQC). The Learning With Errors (LWE) problem \cite{Regev}, due to its strong security guarantees, plays a fundamental role in LBC, although it is not very efficient for cryptographic applications. To address this limitation, several variants of LWE have been developed, such as Ring-LWE (RLWE) \cite{LPR2010}, which is suitable for theoretical purposes, and Polynomial-LWE (PLWE) \cite{BV}, which is more practical. This survey provides a systematic review of vulnerable instances of PLWE. These attacks may extend to RLWE in instances where the two problems are equivalent.. This paper serves as a resource for those seeking a structured overview of the state-of-the-art attacks on PLWE.

FAEST is a post-quantum digital signature candidate whose performance is dominated by repeated AES-CTR-based PRG calls in the VOLE-in-the-Head phase, yet its reference implementation provides no FAEST-specialized ARM NEON acceleration path. We present an ARM-oriented optimization that accelerates this bottleneck using general-purpose NEON SIMD instructions without relying on ARMv8 Crypto Extensions. The proposed implementation combines a register-resident 256-byte S-box with TBL/TBX-based four-stage SubBytes, 4-way and 8-way parallel AES block processing, a fixed-size PRG path specialized for the FAEST tree structure, and pthread-based batch-level parallelization of independent VOLE tasks. Evaluated on all 12 parameter sets of FAEST v2 on Raspberry Pi 4 and Apple M2, the combined optimization achieves speedups of up to $136.9\times$ and $330.1\times$, respectively, over the pure-C reference. On RPi4, the single-thread NEON implementation outperforms OpenSSL's software AES, and on M2, the full NEON-plus-pthread configuration outperforms the best available reference configuration, including hardware-accelerated OpenSSL, across all tested parameters.

The Learning with Errors (LWE) problem has been widely utilized as a foundation for numerous cryptographic tools over the years. In this study, we focus on an algebraic variant of the LWE problem called Group ring LWE (GR-LWE). We select group rings (or their direct summands) that underlie specific families of finite groups constructed by taking the semi-direct product of two cyclic groups. Unlike the Ring-LWE problem described in [LPR10], the multiplication operation in the group rings considered here is non-commutative. As an extension of Ring-LWE, it maintains computational hardness and can be potentially applied in many cryptographic scenarios. In this paper, we present two polynomial-time quantum reductions. Firstly, we provide a quantum reduction from the worst-case shortest independent vectors problem (SIVP) in ideal lattices with polynomial approximate factor to the search version of GR-LWE. This reduction requires that the underlying group ring possesses certain mild properties; Secondly, we present another quantum reduction for two types of group rings, where the worst-case SIVP problem is directly reduced to the (average-case) decision GR-LWE problem. The pseudorandomness of GR-LWE samples guaranteed by this reduction can be consequently leveraged to construct semantically secure public-key cryptosystems.

The rapid advancement of Large Language Models has given rise to autonomous LLM-based agents capable of complex reasoning and execution. As these agents transition from isolated operation to collaborative ecosystems, we witness the emergence of the Agent-to-Agent (A2A) network, a paradigm where heterogeneous agents autonomously coordinate to solve multi-step tasks. While these networks may offer better task performance compared to simply using one agent to complete the entire task, they introduce systemic vulnerabilities, such as adversarial composition, semantic misalignment, and cascading operational failures, that existing agent alignment techniques cannot address. In this vision paper, we argue that the trustworthiness of A2A networks cannot be fully guaranteed via retrofitting on existing protocols that are largely designed for individual agents. Rather, it must be architected from the very beginning of the A2A coordination framework. We present a comprehensive conceptual framework that situates trust in A2A systems through four design pillars.

Graphs $D(n, q)$ and their connected components $CD(n, q)$ were defined 30 years ago. We observe shortly their applications to Extremal Graph Theory, Spectral Graph Theory, Algebraic Graph Theory, Symmetric Cryptography and Theory of Low Density Parity Check Codes. We introduce several new algorithms of Noncommutative Cryptography based on this graphs of large girth, In particular we propose modification of Diffie-Hellman protocol in terms of semigroup of walks of even length on the forest obtained as projective limit of $D(n, q)$ and the homomorphic image of this monoid, acting on the vector space $(F_q)^n$ as transformation group $G(n, q)$ of cubical polynomial transformation. The protocol allows users to elaborate collision vector from $(F_q)^n$ in time $O(n^2)$. The security of this schemes rests on the complexity of Conjugacy Power Problem for affine Cremona semigroup of automorphisms of $F_q[x_1, x_2, \dots, x_n]$. Inverse protocol of El Gamal type allows to use these scheme for encryption or creating of digital signature. Several obfuscations of these algorithm are given.

Quantum cryptographic definitions are often sensitive to the number of copies of the cryptographic states revealed to an adversary. Making definitional changes to the number of copies accessible to an adversary can drastically affect various aspects including the computational hardness, feasibility, and applicability of the resulting cryptographic scheme. This phenomenon appears in many places in quantum cryptography, including quantum pseudorandomness and unclonable cryptography. To address this, we present a generic approach to boost single-copy security to multi-copy security and apply this approach to many settings. As a consequence, we obtain the following new results: • One-copy stretch pseudorandom state generators (under mild assumptions) imply the existence of t-copy stretch pseudorandom state generators, for any fixed polynomial t. • One-query pseudorandom unitaries with short keys (under mild assumptions) imply the existence of t-query pseudorandom unitaries with short keys, for any fixed polynomial t. • Assuming indistinguishability obfuscation and other standard cryptographic assumptions, there exist identical-copy secure unclonable primitives such as public-key quantum money and quantum copy-protection.

We undertake a comprehensive and structured synthesis of the drivers of human behavior in cybersecurity, focusing specifically on people within organizations (i.e., especially employees in companies), and integrate key concepts such as awareness, security culture, and usability into a coherent theoretical framework. This model is then compared with several relevant behavioral models that fundamentally represent drivers of human behavior. Additionally, we discuss how this theoretical framework can help the domain of agentic AI security: We argue that as AI systems increasingly act as autonomous agents within organizations and based on natural language processing, they also exhibit vulnerabilities analogous to human behavioral risks. Consequently, we propose that this human-centric model offers a blueprint for developing additional security strategies against manipulation attacks targeting AI agents.

We present a unifying framework for proving the knowledge-soundness of KZG-like polynomial commitment schemes, encompassing both univariate and multivariate variants. By conceptualizing the proof technique of Lipmaa, Parisella, and Siim for the univariate KZG scheme (EUROCRYPT 2024), we present tools and falsifiable hardness assumptions that permit black-box extraction of the multivariate KZG scheme. Central to our approach is the notion of a canonical Proof-of-Knowledge of a Polynomial (PoKoP) of a polynomial commitment scheme, which we use to capture the extractability notion required in constructions of practical zk-SNARKs. We further present an explicit polynomial decomposition lemma for multivariate polynomials, enabling a more direct analysis of interpolating extractors and bridging the gap between univariate and multivariate commitments. Our results provide the first standard-model proofs of extractability for the multivariate KZG scheme and many of its variants under falsifiable assumptions.

We present a new verifiable oblivious pseudorandom function (VOPRF) from isogeny group actions. Our construction is twice as fast as the previous state of the art of Delpech de Saint Guilhem and Pedersen at a slightly higher communication cost. One major contribution is the realization of a new proof protocol that is integrated as a two-party computation into the OPRF protocol, making the output verifiable. The main design choice behind our construction and this new proof system is to enable an easy transformation into a threshold protocol, something previous designs have not achieved. To this end, we present our VOPRF in a modular way based on different subroutines. We show how to replace these subroutines with their threshold counterparts, using simulation-based arguments. This results in the first threshold VOPRF from isogenies and one of the first threshold VOPRFs in the post-quantum literature. In contrast to other post-quantum threshold VOPRF designs, our construction has input and output size independent of the number of server parties and furthermore is robust, while other designs rely on aborts in the presence of malicious parties.

Remote power analysis is a novel threat to information systems. Under this attack model, the adversary does not require direct physical access to the platform or specialized sensing equipment. Most of the literature in this field deals with advanced acquisition methods and adversarial models. In contrast, side-channel analysis techniques for remote attacks have not been sufficiently explored. We bridge this gap by taking a look at the characteristics of the data recovered from remote power analysis. We use these insights to propose a novel selection rule for correlation-based attacks that boosts success confidence. This improvement comes from the observation that the samples in a power trace are not independent. We show that adjacent samples can also provide useful information by proposing a post-processing step that capitalizes on these additional leakages. In contrast to previous work, the proposed technique does not rely on the selection of points of interest within the power traces. We further investigate the characteristics of "remote" power traces and their effect on the proposed selection rule through experiments with real (TDC, ChipWhisperer) and synthetic data sets. To assess the advantage of the proposed improvement, we also introduce novel performance metrics that divert from known-key evaluation techniques.

We introduce a new (amortized) functional bootstrapping framework over the CKKS homomorphic encryption (HE) scheme based on Fourier extension. While approximating the modular reduction function in CKKS bootstrapping through Fourier series is a well-known technique, how such method can be efficiently generalized to functional bootstrapping is less understood. In this work, we show that, by constructing proper Fourier extensions, any function with a bounded domain in the smoothness class $C^{\kappa}$ can be approximated by a degree-$n$ Fourier series with errors of order $O(n^{-\kappa-2})$ (except at the singularities), improving on previous results on a global error bound of $O(n^{-1})$ [AKP2025]. To achieve such bound, we propose a new way of constructing Fourier extensions, such that the extended functions appear as smooth as possible in the sense of a Fourier approximation. By implementing our functional bootstrapping over OpenFHE, we demonstrate that we can improve the data precision by $10$-$27$ bits and reduce the amortized FBS latency by $1.1$-$2\times$ over a variety of benchmarking functions.

𝑃ℎ𝑜𝑡𝑜𝐷𝑁𝐴 is a widely deployed perceptual hash function used for the detection of illicit content such as Child Sexual Abuse Material (CSAM). This paper presents the first mathematical description of 𝐴𝑙𝑙𝑒𝑔𝑒𝑑 𝑃ℎ𝑜𝑡𝑜𝐷𝑁𝐴, a new function which has identical outputs to that of 𝑃ℎ𝑜𝑡𝑜𝐷𝑁𝐴 for a large database of test images. From this description, several design weaknesses are identified: the algorithm is piece-wise linear and differentiable, the hash value only depends on the sum of the RGB values of each pixel, and it is trivial to find images with hash value equal to all zeroes. The paper further demonstrates that gradient-based optimization techniques and quadratic programming can exploit the mathematical weaknesses of 𝐴𝑙𝑙𝑒𝑔𝑒𝑑 𝑃ℎ𝑜𝑡𝑜𝐷𝑁𝐴 and 𝑃ℎ𝑜𝑡𝑜𝐷𝑁𝐴 to produce visually appealing exact collisions and second preimages; for near-collisions and near-second-preimages the image quality can be further improved. The same techniques can be used to recover the rough shapes of an image from its hash value, disproving the claim from the designer that 𝑃ℎ𝑜𝑡𝑜𝐷𝑁𝐴 is irreversible. Finally, it is also shown that it is easy to produce high-quality perceptually identical images with a hash value that is far from the original image allowing to avoid detection. We have implemented our attacks on a large set of varied images and we have tested them on both 𝐴𝑙𝑙𝑒𝑔𝑒𝑑 𝑃ℎ𝑜𝑡𝑜𝐷𝑁𝐴 and 𝑃ℎ𝑜𝑡𝑜𝐷𝑁𝐴. Our attacks have success rates close or equal to 100% and run in seconds or minutes on a personal laptop; they present a substantial improvement over earlier work that requires hours on parallel machines and that results only in near-collisions. We believe that with additional optimization of the parameters, the image quality and/or the attack performance can be further improved. Our work demonstrates that 𝑃ℎ𝑜𝑡𝑜𝐷𝑁𝐴 is unreliable for the detection of illicit content: it is easy to incriminate someone by sending them false content with a hash value close to illicit content (a false positive) and to avoid detection of illicit content with minimal modifications to an image (a false negative). False positives and leakage of information are particularly problematic in a Client Side Scanning (CSS) scenario as envisaged by several countries, where large hash databases would be stored on every user device and billions of images would be hashed with 𝑃ℎ𝑜𝑡𝑜𝐷𝑁𝐴 every day. Overall, our research cast serious doubts on the suitability of 𝑃ℎ𝑜𝑡𝑜𝐷𝑁𝐴for the large-scale detection of illicit content.

Primitives enabling homomorphic computation over secret-shared values--Homomorphic Secret Sharing (HSS) and algebraic Homomorphic MACs (aHMAC)--have recently emerged as efficient alternatives to ciphertext-based primitives such as fully homomorphic encryption (FHE) and attribute-based encryption (ABE). Leveraging the distributed nature of secret sharing, direct constructions of HSS and aHMAC are simple, lightweight, avoid costly bootstrapping, and have many applications including one-bit-per-gate garbled circuits. Despite encouraging progress, all existing direct schemes still lack one key feature: efficient Single Instruction Multiple Data (SIMD) evaluation, a capability that has been critical to the efficiency of FHE. This gap leaves the potential of substantial efficiency improvements untapped. We present the first SIMD evaluation techniques for HSS and aHMAC, based on variants of the RLWE assumption. Using a new interval coefficient encoding, our approach embeds $\sqrt{n}$ integer-valued slots per ring element and supports $\sqrt{n}$-fold batch addition and multiplication in just $O(\log n)$ ring operations, achieving a multiplicative $\tilde O(\sqrt{n})$ improvement in amortized efficiency over prior direct constructions. Building on top of these improvements, we show a streamlined one-bit-per-gate SIMD garbling scheme with similar efficiency gains in the online phase. Our efficiency gains are concrete. Concrete operation counts and microbenchmark based estimates show $6\times$--$10\times$ improvements in amortized multiplication cost over prior non-SIMD constructions, with up to $25\times$--$50\times$ speedups for aggregation-heavy workloads such as matrix--vector multiplication. These results demonstrate the practical potential of SIMD techniques for secret-sharing-based homomorphic computation.

Ensuring fairness in blockchain-based data trading presents significant challenges, as the transparency of blockchain can expose sensitive details and compromise fairness. Fairness ensures that the seller receives payment only if they provide the correct data, and the buyer gains access to the data only after making the payment. Existing approaches face limitations in efficiency, particularly when applied to large-scale data. Moreover, preserving privacy has also been a significant challenge in blockchain. In this paper, we introduce zkMarket, a privacy-preserving fair trade system on the blockchain. We ensure fairness by integrating encryption with zk-SNARKs, enabling verifiable proofs for fair trading. However, applying zk-SNARKs directly can be computationally expensive for the prover. To address this, we improve efficiency by leveraging our novel matrix-formed PRG (MatPRG) and commit-and-prove SNARK (CP-SNARK), making the data registration process more concise and significantly reducing the seller's proving time. To ensure transaction privacy, zkMarket is built upon an anonymous transfer protocol. Experimental results demonstrate that zkMarket significantly reduces the computational overhead associated with traditional blockchain solutions while maintaining robust security and privacy. Specifically, our evaluation quantifies this high efficiency: the seller can register 1MB of data in 2.8 seconds, the buyer can generate the trade transaction in 0.2 seconds, and the seller can finalize the trade within 0.4 seconds.

Consider a weak analyst that wishes to outsource data collection and computation of aggregate statistics over a a potentially large population of (also weak) clients to a powerful server. For flexibility and efficiency, we consider public-key and non-interactive protocols, meaning the clients know the analyst's public key but do not share secrets, and each client sends at most one message. Furthermore, the final step should be silent, whereby the analyst simply downloads the (encrypted) result from the server when needed. To capture this setting, we define a new primitive we call Non-Interactive Verifiable Aggregation (NIVA). We require both privacy and robustness for a NIVA protocol to be deemed secure. Namely, our security notion for NIVA ensures that the clients' data remains private to both the server and the analyst, while also ensuring that malicious clients cannot skew the results by providing faulty data. We propose a secure NIVA protocol, which we call PEAR (for Private, Efficient, Accurate, Robust), which can validate inputs according to any NP validity rule. PEAR is based on a novel combination of functional encryption for inner-products (Abdalla et al., PKC 2015) and fully-linear probabilistically-checkable proofs (Boneh et al., Crypto 2019). We emphasize that PEAR is non-interactive, public-key, and makes black-box use of the underlying cryptographic primitives. Additionally, we devise substantial optimizations of PEAR for practically-relevant validity rules. Finally, we implement PEAR to show feasibility for such validity rules, conducting a thorough performance evaluation. In particular, we compare PEAR to two more straightforward or "off-the-shelf" NIVA protocols and show performance gains, demonstrating the merit of our new approach. The bottleneck in our protocol comes from the fact that we require the underlying IPFE scheme to be "unrestricted" over a large field. As more efficient such schemes are developed, they can be immediately be plugged into PEAR for further gains.

We present Hardware/Software co-optimization of Hamming Quasi-Cyclic (HQC) enabled by tightly coupled accelerators implemented on a 32-bit Ibex RISC-V core. On the hardware side, we propose a unified multiplier capable of efficiently performing carryless multiplication for both polynomial multiplication over F_2[X]/(X^{n}−1) and multiplication over F_2^{8}. We also design a Keccak permutation accelerator to support efficient randomness sampling. On the software side, we identify the optimal combination of Toom–Cook and Karatsuba methods for efficient polynomial multiplication on the Ibex core and enhance its performance by minimizing the number of memory accesses during its execution.With our co-optimization strategies, our HQC implementation achieves a performance improvement of several tens of times over the reference implementation.

Decentralized lending protocols rely on liquidation mechanisms tied to volatile oracle-derived prices, creating cascading systemic risk during market downturns. We introduce debt-aware discrete bonding curves (DABC)—piecewise-linear bonding curves with a distinguished floor segment whose price is provably non-decreasing. A reserve invariant couples the curve’s collateral to outstanding debt, enabling a credit facility for issuance-native collateral in which borrowing capacity is anchored to the endogenous floor price rather than a market oracle. We prove that no loan originated at or below the floor-anchored LTV can become under-collateralized due to collateral price declines—eliminating protocol-triggered liquidation for this borrowing model. The trade-off: non-repayment results in permanent token lock, not forced sale. By internalizing issuance, trading, and borrowing in a single contract, the mechanism captures fee revenue that would otherwise accrue to external parties, directing it toward floor elevation. A recursive buy-lock-borrow-buy loop enables leveraged positions without liquidation risk; token launches are the most compelling application. To the best of our knowledge, this work provides the first fully formalized treatment in which borrowing safety is derived from a debt-aware reserve invariant and a provably non-decreasing endogenous floor price. We verify the mechanism through stateful fuzz testing and formal verification of a concrete Solidity implementation.

We present an exponential-time key recovery attack on the public-key encryption scheme using matrix codes proposed by Aragon et al. at Asiacrypt 2024. The secret key is a Gabidulin code expanded using an $\mathbb{F}_q$-basis of $\mathbb{F}_{q^m}$ to obtain a matrix code, which is then hidden by appending random rows and columns and by left- and right-multiplication with invertible matrices. Our attack does not rely on the Gabidulin structure and hence applies to most $\mathbb{F}_{q^m}$-linear codes hidden by their transform. Its complexity is better than the previously best-known distinguisher and significantly better than the naive key recovery algorithm. Our attack breaks some of their proposed parameters. For example, a parameter set targeting 192-bit security is reduced to about 161 bits, and a 256-bit set to about 223 bits.

In this work, we present new cryptanalytic attacks on recently proposed, theory-inspired constructions of weak pseudorandom functions (weak-PRFs). We demonstrate attacks on several such designs, showing that the initial security arguments require significant refinement. Methodologically, our approach relies on novel observations about the structure of cyclic matrices, applications of Wagner's generalized birthday technique, and conversion into polynomial systems over $\mathbb{F}_3$. These findings highlight the need for a more careful analysis of those weak-PRF candidates

Certified deletion ensures that encrypted data can be irreversibly deleted, preventing future recovery even if decryption keys are later exposed. Although existing works have achieved certified deletion across various cryptographic primitives, they rely on central authorities, leading to inherent escrow vulnerabilities. This raises the question of whether certified deletion can be achieved in decentralized frameworks such as Registered Attribute-Based Encryption (RABE) that combines fine-grained access control with user-controlled key registration. This paper presents the first RABE schemes supporting certified deletion and certified everlasting security. Specifically, we obtain the following: - We first design a privately verifiable RABE with Certified Deletion (RABE-CD) scheme by combining our newly proposed shadow registered ABE (Shad-RABE) with one-time symmetric key encryption with certified deletion. - We then construct a publicly verifiable RABE-CD scheme using Shad-RABE, witness encryption, and one-shot signatures, allowing any party to validate deletion certificates without accessing secret keys. - We also extend to privately verifiable RABE with Certified Everlasting Deletion (RABE-CED) scheme, integrating quantum-secure RABE with the certified everlasting lemma. Once a certificate is produced, message privacy becomes information-theoretic even against unbounded adversaries. - We finally realize a publicly verifiable RABE-CED scheme by employing digital signatures for the BB84 states, allowing universal verification while ensuring that deletion irreversibly destroys information relevant to decryption.

We present Remise, a two-server authorized anonymous communication system built on Distributed Oblivious RAM (DORAM). Remise supports two modes of opera- tion: (i) an anonymous bulletin board, where messages are publicly revealed at the end of each epoch without linking senders to messages, and (ii) anonymous commu- nication channels, where messages remain secret-shared, and writers selectively grant and revoke read access to chosen readers. In both modes, the two servers execute read and write operations without learning which indices are accessed, which authorization tokens are used, or which relationships exist between writers and readers, assuming at least one honest server. A central contri- bution of Remise is a lightweight and efficient access- control mechanism. Authorization proofs are maintained in secret-shared form across the two servers, enabling oblivious verification while preventing leakage even un- der client–server collusion. Unlike prior DPF-based sys- tems, Remise provides built-in auditing by having the semi-honest servers generate standard-basis vector shares internally, eliminating the need for server-side DPF va- lidity checks. We implement a prototype of Remise and evaluate it under realistic network conditions. Our ex- periments show 80×improvement in online server time when compared to PACL (Spectrum) (IEEE S&P 2023) for databases of size $22^{24}$

We present CHOPIN, a pairing-based multilinear polynomial commitment scheme (PCS) achieving constant proof size and a linear-time prover, constructed modularly from a bivariate PCS. CHOPIN generalizes the recent compilers from univariate to multilinear PCS MERCURY (Eagen and Gabizon, ePrint 2025/385) and Samaritan (Ganesh, Patranabis, and Singh, ASIACRYPT 2025). Due to its modular design, we obtain a direct proof of knowledge soundness via a reduction to the knowledge soundness of the underlying bivariate PCS in the standard model. In particular, our analysis avoids idealized models such as the Algebraic Group Model. When instantiated with the bivariate KZG scheme (Papamanthou, Shi, and Tamassia, TCC 2013), CHOPIN achieves a similar proof size to Mercury and Samaritan while offering a two-fold speedup in the main bottleneck for the prover time, which arises because CHOPIN requires only a single large MSM proportional to the size of the committed multilinear polynomial, in contrast to the two large MSMs required by the prior works, at the cost of one additional pairing for the verifier.

We propose Libra, a compiler framework that automates efficient code generation for cross-scheme fully homomorphic encryption (FHE) on highly parallel computing architectures. While it is known that leveraging multiple FHE schemes in a single application can improve the overall efficiency, the exact mapping of cross-scheme FHE operators onto high-performance architectures, such as general-purpose graphic processing units (GPGPUs), remains challenging. To address such challenge, Libra integrates both the FHE computational patterns and hardware-aware scheduling strategies to establish an algorithm-hardware co-optimization framework. Specifically, Libra defines a novel cross-scheme representation for FHE that abstracts common program patterns for each of the FHE schemes. Then, we dynamically optimize the output FHE program based on the combined execution costs of FHE primitives derived from multiple scheme switching patterns. Next, to accelerate inter-operator execution on GPUs, Libra introduces a computational scheduling strategy that bridges high-level computation characteristics with low-level execution plans. Through the proposed pattern-scheduling co-optimization process, Libra generates efficient codes for cross-scheme high-precision FHE computations on GPGPUs. Experiment results show that Libra achieves up to 270$\times$ speedup on microbenchmarks and 19$\times$ on the applications compared to state-of-the-art cross-scheme, while improving compute unit and memory bandwidth utilization by $44\%$ and $36.1\%$.

We present a new framework for secure computation of arithmetic circuits with two-thirds honest majority that lifts semi-honest protocols to full malicious security. Our framework works with any linear secret sharing over any finite ring and maintains the type of security of the underlying semi-honest protocol (i.e., computational or information-theoretic). The framework has the following overhead complexity with respect to size \(|C|\) of the computed circuit \(C\): it incurs only logarithmic communication overhead in \(|C|\) over the cost of the semi-honest protocol, the number of additional rounds is independent of the circuit's size, and the computational work per party is \(O(|C|)\) arithmetic operations. Even when limiting the scope to static adversaries, previous works could only achieve two of these three measures: Either the communication is logarithmic and the computational overhead per party is \(O(|C|)\), but the number of additional rounds grows with the circuit's size, or communication is logarithmic and the number of rounds is \(O(n)\), but the computational overhead is \(O(n\cdot |C|)\). To the best of our knowledge, we are the first to achieve the desired complexity in all three fronts, making the cost of achieving full security in MPC lower than ever. Our result is achieved via a new verification technique based on a robust recursive search that finds and removes cheaters from the computation. We further improve our result by reducing costs associated with the number of parties~\(n\). While the initial result incurs cubic communication overhead with respect to \(n\) and \(O(n)\) additional rounds in the worst case, we show how to reduce it to \(\sqrt{n^5}\) communication overhead and \(O(\sqrt{n\log\log n})\) additional rounds, without sacrificing the computational overhead, which remains \(O(|C|)\). This is achieved via a novel technique we call gap amplification that accelerates the player elimination process, enabling us to reduce the number of calls to the verification subprotocol. This technique is of independent interest as it is general and can be directly applied to any protocol that relies on player elimination.

At CRYPTO 2009, Heninger and Shacham presented a branch-and-prune algorithm for reconstructing an RSA private key given a random fraction of its private components. This method has been widely adopted in side-channel attacks, and its complexity is closely related to the specific leakage pattern encountered. In this work, we propose a new leakage model that enables efficient key reconstruction by exploiting a vulnerability in the modular exponentiation invoked by OpenSSL's implementation of Miller-Rabin primality test. This vulnerability reveals the least significant $b$ bits of each window. Through our proposed model, these bits form new leakage patterns, which we term aligned and misaligned. In particular, the misaligned case includes previously undocumented scenarios where full key recovery is achievable without branching. Then we analyze the global and local behavior of key reconstruction under these patterns. Our evaluation demonstrates that they yield more efficient key reconstruction and maintain this advantage even in the presence of additional erasures. Moreover, in specific scenarios, successful reconstruction remains practical even if the bits obtained are less than 50\%. Finally, we conducted a series of experiments to confirm the practicality of our work, successfully recovering the lower 4 bits from each 6-bit window and demonstrating efficient key reconstruction under our model.

In this work, we consider dishonest majority MPC protocols with $(1-\epsilon)n$ corrupted parties for some constant $\epsilon\in (0,1/2)$. In this setting, there exist MPC protocols with unanimous abort that achieve constant communication in both online and offline phases via a packed secret sharing scheme. Departing from their approaches, we revisit the ''committee-based'' approach to design an efficient MPC protocol with constant online and offline communication complexity. To balance the communication load of each party, our protocol adopts multiple committees, each of constant size. The computation of circuit $C$ is then divided into layers, each assigned to one committee. To securely transmit messages between committees, we introduce the handoff gates, incurring only a slight communication overhead. Furthermore, we leverage circuit-dependent preprocessing and incremental checking to improve the online efficiency. Compared to other MPC protocols in the same corruption setting, our protocol achieves the smallest concrete total communication complexity. Building upon our multi-committee unanimous-abort protocol, we upgrade it to identifiable abort by adapting a technique from (Rivinius, EUROCRYPT 2025). To integrate this technique into our setting, we adjust the verification timing and introduce a king party to reduce the communication complexity of openings. This yields the first identifiable-abort MPC protocol with constant communication complexity in the sub-optimal dishonest majority setting.

LESS is a digital signature scheme that is currently in the second round of the National Institute of Standards and Technology’s (NIST’s) ongoing call for standardization of additional post-quantum signature schemes. Recently, the ZKfault attack by Mondal et al. (Asiacrypt 2024) showed several attack surfaces on the first version of LESS (LESS-v1) that can be exploited using different fault attacks. However, the designers of LESS have updated the scheme in the second round to improve efficiency and signature size. The fault attacks in ZKfault are not directly applicable to this new version of LESS (LESS-v2). The physical security of LESS-v2 is still unexplored. In this work, we analyze the new structure of the LESS-v2 signature scheme and propose a method for universal forgery. One crucial observation is that, for LESS-v2, an adversary does not require the full signing key, but some other secret-related information, namely, a permutation of secret monomial matrices. We assume an adversary can use execution interruption techniques, such as fault attacks, to recover this extra information. We have analyzed multiple such attack surfaces in the design of LESS-v2, and using fault injection, we can recover secret-related information. We showed the average number of required faults for two particular fault models to recover the secret equivalent component and observed that, for most parameters, we need only 1 faulted signature, and at most 1088. Our attacks rely on simple and standard fault models. We demonstrated these using both simulation and a simple experimental setup.

Polynomial commitment schemes (PCSs) are a core primitive in modern proof systems, especially SNARKs. Lattice-based PCSs are a natural post-quantum alternative, but existing constructions typically enforce lattice smallness only up to a multiplicative slack in the extracted $\ell_2$ norm. We present Serval, a lattice-based PCS with \emph{slack-free} $\ell_2$ soundness (norm-preserving extraction) under standard SIS/LWE-type assumptions. Following the norm-proof paradigm of Lyubashevsky~\etal (Crypto~'22), we reduce exact $\ell_2$ enforcement to a self-inner-product argument plus a binary validation that avoids modular wraparound. Our main technical insight is a reduction that rewrites the binary check as inner-product-shaped constraints that match the algebraic form of the PCS evaluation and commitment-consistency checks. This alignment yields a unified divide-and-conquer protocol that proves all constraints simultaneously in $O(\log L)$ rounds, giving succinct evaluation proofs and efficient verification. At $L = 2^{20}$ and matched security parameters ($\lambda = 128$), our instantiated proof size is $8 \times$ smaller than Fenzi~\etal (JoC~'24) and $85 \times$ smaller than SLAP (Eurocrypt~'24), while remaining compatible with the recent construction of Cini~\etal (Crypto~'24).

ML-DSA (formerly CRYSTALS-Dilithium), the primary NIST post-quantum signature standard, relies on rejection sampling to ensure that released signatures are statistically independent of the secret key. Recent work by Liu et al. and Damm et al. showed that this protection breaks down as soon as an attacker obtains even a single bit of the generated masking randomness per signature, enabling key recovery via linear regression over the resulting noisy linear system. However, this regression approach requires the attacker to collect a large number of such leaky signatures—up to 2.4 million so-called informative relations for ML-DSA-65—thereby limiting the attack’s practical applicability. We dramatically reduce this cost by reformulating the key recovery as a constraint-satisfaction problem solvable by local optimization. Our approach rests on two contributions. First, we construct a verification routine that checks candidate subkeys using only the collected leakage relations, i.e. without knowledge of the remaining secret-key components or relying on computation-intensive reductions. Second, building on theoretical insights from this verification method, we design a multi-tier hill-climbing algorithm that iteratively refines candidates by minimizing a scoring function. In the exact leakage setting, our attack recovers ML-DSA subkeys from as few as 5 000 to 35 000 informative relations across all parameter sets and leakage bit indices the attack is applicable for, constituting a reduction by a factor of 37–68× over the previous state of the art. We further extend the attack to a noisy leakage model, where the leaked bit is flipped independently with error probability p. We demonstrate experimentally that key recovery remains feasible even at noise rates as high as 45%, again with substantially fewer leakage information than prior work.

Lookup arguments are a key technique in SNARKs for reducing the cost of operations which are “arithmetization-unfriendly”, such as range checks and bitwise comparisons. The idea is to encode the valid outputs of the operation in a publicly known table, and then prove that every element of the SNARK witness belongs to the table. Existing constructions for lookup arguments, however, are designed for working over fields, making them incompatible with recent post-quantum lattice-based schemes that operate over rings. In this work we formalize lookup arguments over rings for tables containing arbitrary ring elements. We bring attention to systematic issues that arise when translating techniques from fields to rings by showing several known lookup arguments are susceptible to attacks. We then extend two central polynomial IOPs, Plookup and LogUp, over the ring $\mathcal{R} = \mathbb{Z}_q[X]/(X^d + 1)$, and show how to compile them with polynomial commitments based on lattice assumptions to get succinct lattice-based lookup arguments. We additionally show how to apply ring lookups to obtain succinct arguments for batch-verification of RAM updates where the RAM entries are arbitrary ring elements.

We present a novel protocol for two-party ECDSA that achieves two rounds (a single back-and-forth communication) at the cost of a single oblivious linear function evaluation (OLE). In comparison, the previous work of Boneh et al.~(EUROCRYPT 2025) achieves two rounds but requires expensive zero-knowledge proofs on top of the OLE. We demonstrate this by proving that in the generic group model, any adversary capable of generating forgeries for our protocol can be transformed into an adversary that finds preimages for the ECDSA message digest function (e.g., the SHA family). Interestingly, our analysis is closely related to, and has ramifications for, the `presignatures' mode of operation---Canetti et al.~(CCS 2020), Groth and Shoup (EUROCRYPT 2022). Motivated by applications to embedded cryptocurrency wallets, where a single server maintains distinct, shared public keys with separate clients (i.e., a star-shaped topology), and with the goal of minimizing communication, we instantiate our protocol using Paillier encryption and suitable zero-knowledge proofs. To reduce computational overhead, we thoroughly optimize all components of our protocol under sound cryptographic assumptions, specifically small-exponent variants of RSA-style assumptions. Finally, we implement our protocol and provide benchmarks. At the 128-bit security level, the signing phase requires approximately 50ms of computation time on a standard linux machine, and 2KB of bandwidth.

One approach to solving polynomial systems is to multiply each equation by monomials, which creates a larger system with the coefficient matrix known as the Macaulay matrix. The eXtended Linearization (XL) method, introduced by Courtois, Klimov, Patarin, and Shamir in 2000, is one such approach and includes a sub-algorithm that performs Gaussian elimination on the Macaulay matrix. Due to the simplicity of the method, several improvements and variations have been proposed since its introduction, and it remains an active area of research. In this paper, we focus on sub-algorithms based on Macaulay matrices that appear in the XL method and its variants and investigate input parameters that yield desired outputs such as Gr\"{o}bner bases. In particular, by revisiting the standard degree setting and formulating a framework without fixing a specific monomial order, we provide a foundation for extending the analysis to the multi-degree case.

In this note, we demonstrate that the construction of asynchronous complete secret sharing (ACSS) proposed in the recent work by Qin et al., accepted at Eurocrypt 2026, is insecure. In particular, we identify several issues affecting the liveness of their protocol and present attacks that compromise its correctness.

SQIsign is an isogeny‑based post‑quantum signature scheme over supersingular elliptic curves that represents isogenies as elements of a quaternion algebra, enabling highly compact signatures and efficient computation. However, because SQIsign performs quaternion arithmetic over $\mathbb{Q}$, no explicit, uniform worst‑case bound is available for the integer coefficients used to represent quaternion algebra elements. Hence, existing implementations require multi-precision integer arithmetic which hinders portability and complicates memory management, disabling constant-time and embedded-friendly implementations. In this work, we perform a complete analysis of all routines in the Round-2 SQIsign specification that manipulate quaternion elements and establish an explicit uniform worst‑case size bound, with a hypothesis to make all intermediate quaternion computations provably bounded. This proof removes the need for multi-precision arithmetic, enabling the first implementation of SQIsign with fixed-precision integer arithmetic, further presenting possibility of constant-time and memory-friendly implementation. We further tighten this bound by introducing a modified ideal multiplication algorithm, which is a subroutine of SQisign. By modifying the ideal multiplication, we derived the improvement of the size of uniform bound compared with the experimental maximum bit of original Round-$2$ SQIsign, as $45\%/44\%/44.5\%$, for NIST-I/III/V security levels, respectively. Relying on the reduced uniform bound, we build a fixed-precision C implementation of SQIsign.

In applications such as secure group communication and broadcasting, it is important to efficiently deliver multiple messages to different recipients at once. To this end, multi-message multi-recipient Public Key Encryption (mmPKE) enables the batch encryption of multiple messages for multiple independent recipients in one go, significantly reducing costs–particularly bandwidth–compared to the trivial solution of encrypting each message individually. This capability is especially desirable in the post-quantum setting, where the ciphertext length is typically significantly larger than the corresponding plaintext. However, almost all prior works on mmPKE are limited to quantum-vulnerable traditional assumptions. In this work, we propose the first CPA-secure mmPKE and Multi-Key Encapsulation Mechanism (mmKEM) from the standard Module Learning with Errors (MLWE) lattice assumption, named mmCipher-PKE and mmCipher-KEM, respectively. Our design proceeds in two steps: (i) We introduce a novel generic construction of mmPKE by proposing a new PKE variant—extended reproducible PKE (XR-PKE)—that enables the reproduction of ciphertexts through additional hints; (ii) We instantiate a lattice-based XR-PKE using a new technique that can precisely estimate the impact of such hints on the ciphertext security while also establishing suitable parameters. We believe both to be of independent interest. As a bonus contribution, we explore generic constructions of adaptively secure mmPKE, resisting adaptive corruption and chosen-ciphertext attacks. We also provide an efficient implementation and thorough evaluation of the practical performance of our mmCipher. The results demonstrate substantial bandwidth and computational savings over the state-of-the-art. For example, for 1024 recipients, our mmCipher-KEM achieves a 23-45× reduction in bandwidth overhead, with ciphertexts only 4-9% larger than the plaintexts (near optimal bandwidth), while also offering a 3-5× reduction in computational cost.

The algebraic group model (AGM), formalized by Fuchsbauer, Kiltz, and Loss (Crypto 2018), has recently garnered significant attention. Notably, Katz, Zhang, and Zhou (Asiacrypt 2022) challenged a widely held belief: that hardness results proven in the AGM imply corresponding results in the generic group model (GGM). They showed that this implication fails under Shoup's GGM framework. In response, Jaeger and Mohan (Crypto 2024) proposed an alternative interpretation based on Maurer's GGM and proved that, under this interpretation, the implication indeed holds. Many cryptographic applications analyzed in the AGM also rely on the random oracle model (ROM), which is largely absent from Jaeger and Mohan's framework. Because Maurer’s GGM and the ROM are inherently incomparable, Jaeger and Mohan's framework may not capture all AGM-based proofs. To bridge this gap and faithfully translate all known AGM-based proofs into the GGM setting, we make the following contributions: - Limitations of JM's framework: Jaeger and Mohan’s framework captures only those primitives that can be instantiated within Maurer’s GGM. We identify a primitive—specifically, a public-key encryption scheme with short ciphertexts—whose security has been analyzed in the AGM, and establish a black-box separation between this primitive and Maurer’s GGM, even when combined with the ROM. This result provides concrete evidence that JM’s framework cannot encompass all known AGM-based proofs. - Augmented framework: We propose an augmented framework that integrates Maurer’s GGM with a carefully constructed ROM, enabling inputs and outputs to incorporate group elements defined within Maurer’s model. - Transferring all known AGM-based proofs to GGM setting: Building on our augmented framework, we prove the lifting lemma from the AGM to our model, demonstrating that hardness results in the AGM+ROM directly carry over to our setting, thereby justifying all known AGM-based proofs.

We propose new techniques for estimating the probability that an input difference leads to an output difference in a block cipher (i.e., the probability of a differential) under the assumption of independent round-keys. We apply our techniques to AES, and show that the probability of every non-trivial differential in 8-round AES is within an additive factor of $2^{-128} \cdot \frac{1}{50}$ from the expected value of $\frac{1}{2^{128} - 1}$. We further apply our techniques to prove that 40-round AES is at most $2^{-135}$-close to a pairwise independent permutation. This improves upon the work of Liu, Tessaro and Vaikuntanathan [CRYPTO 2021], who proved a similar bound for 9000-round AES. To obtain our results, we develop and adapt a variety of techniques for analyzing differentials using functional analysis. We expect these techniques to be useful for analyzing differentials in additional block ciphers besides the AES.

Can we hope to provide provable security against model extraction attacks? As a step towards a theoretical study of this question, we unify and abstract a wide range of "observational" model extraction defenses (OMEDs) --- roughly, those that attempt to detect model extraction by analyzing the distribution over the adversary's queries. To accompany the abstract OMED, we define the notion of complete OMEDs --- when benign clients can freely interact with the model --- and sound OMEDs --- when adversarial clients are caught and prevented from reverse engineering the model. Our formalism facilitates a simple argument for obtaining provable security against model extraction by complete and sound OMEDs, using (average-case) hardness assumptions for PAC-learning, in a way that abstracts current techniques in the prior literature. The main result of this work establishes a partial computational incompleteness theorem for the OMED: any efficient OMED for a machine learning model computable by a polynomial size decision tree that satisfies a basic form of completeness cannot satisfy soundness, unless the subexponential Learning Parity with Noise (LPN) assumption does not hold. To prove the incompleteness theorem, we introduce a class of model extraction attacks called natural Covert Learning attacks based on a connection to the Covert Learning model of Canetti and Karchmer (TCC '21), and show that such attacks circumvent any defense within our abstract mechanism in a black-box, nonadaptive way. As a further technical contribution, we extend the Covert Learning algorithm of Canetti and Karchmer to work over any "concise" product distribution (albeit for juntas of a logarithmic number of variables rather than polynomial size decision trees), by showing that the technique of learning with a distributional inverter of Binnendyk et al. (ALT '22) remains viable in the Covert Learning setting.

SNARKs work by having a prover commit to a witness and then prove that the committed witness is valid. The prover’s work is dominated by two tasks: (i) committing to data and (ii) proving that the committed data is well-formed. The central thesis of this survey is that fast SNARKs minimize both costs by using the sum-check protocol. But not all uses of sum-check are equally effective. The fastest SNARKs invoke sum-check in highly sophisticated ways, exploiting repeated structure in computation to aggressively minimize commitment costs and prover work. I survey the key ideas that enable this: batch evaluation arguments, read/write memory checking, virtual polynomials, sparse sum-checks, and small-value preservation. These techniques unlock the full potential of the sum-check protocol as a foundation for fast SNARK proving.

We study whether Verifiable Delay Functions (VDFs) can be constructed in the (plain) Random Oracle Model (ROM) without any computational assumptions. A first partial answer to this question is due to Mahmoody, Smith, and Wu [ICALP 2020] where they rule out perfectly unique VDFs in the ROM. Building on this result, Guan, Riazanov, and Yuan [CRYPTO 2025] prove that VDFs with computational uniqueness and public-coin setup are impossible in the ROM. These works leave open the possibility of constructing computationally unique VDFs with private-coin setup in the ROM. We resolve this problem and additionally rule out computationally-unique VDFs with computationally expensive private-coin setup in the ROM.

This survey article provides an overview of the Semigroup Action Problem (SAP) as a pivotal generalization of the Discrete Logarithm Problem (DLP), tracing its theoretical evolution from foundational algebraic cryptography in the early 2000s to its application in the National Institute of Standards and Technology (NIST) Post-Quantum Cryptography (PQC) standardization process. We examine the mathematical framework of semigroup actions, contrasting them with classical group-theoretic assumptions, and detail the generalizations of Diffie-Hellman and ElGamal protocols within this broader context. Finally, the paper investigates the renaissance of group and semigroup actions in the design of next-generation digital signatures, providing a detailed algebraic analysis of candidates in the current NIST competition.

Hamming Quasi-Cyclic (HQC) is a leading code-based key-encapsulation mechanism (KEM), recently selected by NIST for standardization, whose bandwidth and efficiency are balanced with the concrete cost of information-set decoding (ISD) attacks. However, the current balance relies on (1) the decryption-failure-rate (DFR) is directly configured to be less than $2^{-\lambda}$ ($\lambda$ is the security parameter), rather than carefully determined by choosing conservative parameters to resist known attacks as the Kyber team did in the design of NIST FIPS 203; (2) the error distribution in the underlying quasi-cyclic syndrome decoding problem is restricted to be balanced. In this paper, we show how to quantitatively and conservatively evaluate the impact of removing the aforementioned two restrictions on the complexities of known attacks, and thus find a new balance among bandwidth, efficiency, and security for HQC. In detail, we first formalize the best-known decryption-failure attack against HQC, and derive an upper bound on the probability that an adversary triggers a decryption-failure event under realistic query and time limits, enabling an attack-aware upper bound on the secure DFR. Second, we quantify how the weight distribution of $(\mathbf{r}_1, \mathbf{r}_2, \mathbf{e})$ (the random low-weight polynomials used in encryption) affects the concrete cost of ISD attacks and DFR. This yields an \emph{unbalanced} weight strategy that strictly lowers the DFR without sacrificing the targeted bit security, leading to a new variant called \emph{Unbalanced HQC (UHQC)}. By combining these analyses, we provide optimized parameters for UHQC. Across all NIST security levels, UHQC reduces bandwidth by 10-12% and improves runtime by 6-8%.

A useful linearization technique (or a trick) was introduced in the Marlin and Plonk SNARKs, which significantly reduces the number of KZG polynomial commitment openings a SNARK prover has to send. Subsequently, many other KZG-based protocols have taken advantage of it. We revisit and formalize this technique: – We define a Linearization Polynomial Commitment Scheme (LPCS) that abstracts their linearization technique. – We formalize LinKZG, a LPCS version of the KZG commitment scheme, and show that it achieves a weak form of extractability under a target group version of the ARSDH assumption. We show that Plonk is secure under the same assumption in the ROM. – We show how to construct LPCSs from any homomorphic polynomial commitment scheme. Thus, enabling the linearization technique also for those polynomial commitment schemes, and potentially improving the efficiency of many other SNARKs.

Distributed key generation (DKG) protocols enable a set of parties to distributively generate a threshold-shared key pair \((\mathsf{pk}, \mathsf{sk})\), such that at least \(t\) parties must participate to reconstruct the secret. We introduce the first DKG protocol for discrete-logarithm based keys that are both universally composable and adaptively secure without erasure, inconsistent players, interactive assumptions, or oracle-aided simulation. Our contributions are as follows: (1) an adaptively secure and universally composable DKG that achieves guaranteed output delivery in three rounds assuming an honest majority, (2) an adaptively secure and universally composable committed DKG that realizes our novel committed DKG functionality, tolerates a full corruption threshold, and achieves identifiable abort in two rounds, (3) an adaptively secure and universally composable committed DKG that achieves guaranteed output in three rounds assuming an honest majority, (4) as an application, an incredibly simple threshold Schnorr protocol in the committed DKG-hybrid model--implying an adaptively secure and universally composable threshold Schnorr protocol tolerating a full corruption threshold with identifiable abort in three rounds, and an adaptively secure and universally composable threshold Schnorr protocol for an honest majority with guaranteed output in four rounds. Most importantly, our DKG constructions are secure in the random oracle model under the DDH assumption. Our output guarantees are proven under the assumption of synchrony. All existing synchronous DKG protocols for discrete-logarithm based keys satisfy weaker security notions or require stronger assumptions.

This paper formally specifies and analyzes the CK hybrid key encapsulation mechanism (KEM) construction from the IRTF CFRG’s recent draft on hybrid (post-quantum/traditional) KEMs CK combines two KEMs using a PRF to produce a hybrid KEM. Unlike the QSF framework of Barbosa et al., which combines an IND-CCA KEM with a nominal group (Diffie-Hellman-style), CK combines a C2PRI-secure post-quantum-secure KEM with an IND-CCA traditionlly-secure KEM constructed from an IND-CCA2 public key encryption (PKE) scheme, such as RSA-OAEP. We additionally show how to securely promote an IND-CCA2 PKE into an IND-CCA KEM. We perform two complementary security analyses of CK in the standard model: the first shows CK is IND-CCA assuming the traditional KEM is IND-CCA, the post-quantum KEM is C2PRI, and the KDF is a secure PRF; the second shows CK is IND-CCA assuming the post-quantum KEM is IND-CCA and the KDF is a secure PRF, even if the traditional KEM is completely broken. Neither proof requires the random oracle model.

Polynomials are a fundamental mathematical object underlying virtually all of theoretical computer science. In proof systems, a common task for the verifier is to evaluate a polynomial of degree $d$ at $m$ distinct points. The best known algorithm for this problem performs $O((m + d) \cdot \log^2(m + d))$ field operations. We present a concretely efficient $\mathsf{MA}$ protocol for this problem in which the verifier runs in \emph{linear time}: the prover sends a single message consisting of $d - 1$ field elements, and the verifier performs only $O(m + d)$ field operations. We further extend our protocol to handle the more general setting of evaluating multiple polynomials at multiple points, and for this problem, we construct an $\mathsf{AMA}$ protocol. Our protocols improve the verifier time in several interactive proofs. Most notably are the sumcheck protocol over a large summation domain and protocols that rely on polynomial quotienting. In particular, by a straightforward application of our results, we reduce the verifier's runtime in the STIR protocol (CRYPTO 2024) to match that of WHIR (EUROCRYPT 2025), despite WHIR being highly optimized for verification time. As an additional application, we show that any univariate polynomial commitment schemes (PCS) can be transformed, in a black-box manner, into a new scheme that efficiently supports batch openings at multiple points. In particular, opening $m$ points incurs only a constant overhead compared to opening a single point.

In fully homomorphic encryption, bootstrapping serves as a key component while also remaining the performance bottleneck of the scheme. Specifically, for CKKS bootstrapping, this bottleneck is reflected in significant computational overhead and modulus consumption. In this work, we improve the CKKS bootstrapping with lower time complexity and less modulus consumption. We first propose a novel rescaling operation, called level-conserving rescaling, that acts on CoeffsToSlots for saving moduli. Secondly, we reconstruct the rotation keys and merge the plaintext-ciphertext multiplication and rescaling operations into the key-switching procedure, which reduces the time complexity of matrix-vector multiplication for matrices with $\le$64 non-zero diagonals, albeit with increased space overhead. By combining the two methods in CoeffsToSlots in a non-trivial manner, we not only further accelerate the homomorphic linear transformations and save one level of moduli, but also reduce the total size of rotation keys. Experiments demonstrate the practicability of our techniques. Compared to the state of the art, our approaches save one level of moduli, achieving a $20\%\sim 35\%$ improvement in bootstrapping throughput and an 11.9\% $\sim$ 15.2\% reduction of rotation key size in CoeffsToSlots. Furthermore, with sufficient storage, our technology achieves up to 40\% higher bootstrapping throughput than before, at the cost of doubling the rotation key size in CoeffsToSlots. The bootstrapping precision and failure probability remain identical to the previous method.

Most prior works on secure Multi-Party Computation (MPC) in asynchronous networks study Guaranteed Output Delivery (GOD), meaning that all parties learn the function output. Asynchronous MPC protocols with GOD necessarily tolerate only t < n/3 corruptions, and they necessarily allow the adversary to exclude the inputs of up to t honest parties from the computation, a phenomenon referred to as input loss. Seeking improvements to threshold/input loss, we consider weakening GOD to security with abort, a standard notion studied in the context of synchronous networks. Unfortunately we show that, when these standard notions are applied in asynchrony, it is not possible to improve the corruption threshold or the input loss. We therefore study relaxations of these standard notions under which protocols can be improved. In particular, we propose a relaxation of the standard notion of correctness for asynchronous MPC protocols. Our relaxed notion requires only that parties obtain the correct output when all parties are honest and when at most a threshold A of the parties are asynchronous. We present several impossibility and feasibility results that completely characterize what is possible in the context of our relaxed correctness. For instance, it is possible to achieve selective abort even when t < n parties are corrupt if (and only if) A < (n-t)/2, but it is impossible to achieve unanimous abort unless t < n/3, even when A=0. We additionally propose a new notion of identifiable abort for asynchronous networks (aIA), and we show that we can achieve fair MPC with aIA and min(A,t) input loss.