Proof-of-stake consensus protocols often rely on distributed randomness beacons (DRBs) to generate randomness for leader selection. This work analyses the manipulability of Ethereum's DRB implementation, RANDAO, in its current consensus mechanism. Even with its efficiency, RANDAO remains vulnerable to manipulation through the deliberate omission of blocks from the canonical chain. Previous research has shown that economically rational players can withhold blocks --~known as a block withholding attack or selfish mixing~-- when the manipulated RANDAO outcome yields greater financial rewards. We introduce and evaluate a new manipulation strategy, the RANDAO forking attack. Unlike block withholding, whereby validators opt to hide a block, this strategy relies on selectively forking out an honest proposer's block to maximize transaction fee revenues and block rewards. In this paper, we draw attention to the fact that the forking attack is significantly more harmful than selfish mixing for two reasons. Firstly, it exacerbates the unfairness among validators. More importantly, it significantly undermines the reliability of the blockchain for the average user by frequently causing already published blocks to be forked out. By doing so, the attacker can fork the chain without losing slots, and we demonstrate that these are later fully compensated for. Our empirical measurements, investigating such manipulations on Ethereum mainnet, revealed no statistically significant traces of these attacks to date.

It is imperative to modernize traditional core cryptographic primitives, such as Oblivious Transfer (OT), to address the demands of the new digital era, where privacy-preserving computations are executed on low-power devices. This modernization is not merely an enhancement but a necessity to ensure security, efficiency, and continued relevance in an ever-evolving technological landscape. This work introduces two scalable OT schemes: (1) Helix OT, a $1$-out-of-$n$ OT, and (2) Priority OT, a $t$-out-of-$n$ OT. Both schemes provide unconditional security, ensuring resilience against quantum adversaries. Helix OT achieves a receiver-side download complexity of $O(1)$. In big data scenarios, where certain data may be more urgent or valuable, we propose Priority OT. With a receiver-side download complexity of $O(t)$, this scheme allows data to be received based on specified priorities. By prioritizing data transmission, Priority OT ensures that the most important data is received first, optimizing bandwidth, storage, and processing resources. Performance evaluations indicate that Helix OT completes the transfer of 1 out of $n=$ 16,777,216 messages in 9 seconds, and Priority OT handles $t=$ 1,048,576 out of $n$ selections in 30 seconds. Both outperform existing $t$-out-of-$n$ OTs (when $t\geq 1$), underscoring their suitability for large-scale applications. To the best of our knowledge, Helix OT and Priority OT introduce unique advancements that distinguish them from previous schemes.

Unprotected cryptographic implementations are vulnerable to implementation attacks, such as passive side-channel attacks and active fault injection attacks. Recently, countermeasures like polynomial masking and duplicated masking have been introduced to protect implementations against combined attacks that exploit leakage and faults simultaneously. While duplicated masking requires $O(t * e)$ shares to resist an adversary capable of probing $t$ values and faulting $e$ values, polynomial masking requires only $O(t + e)$ shares, which is particularly beneficial for affine computation. At CHES'$24$, Arnold et al. showed how to further improve the efficiency of polynomial masking in the presence of combined attacks by embedding two secrets into one polynomial sharing. This essentially reduces the complexity of previous constructions by half. The authors also observed that using techniques from packed secret sharing (Grosso et al., CHES'$13$) cannot easily achieve combined resilience to encode an arbitrary number of secrets in one polynomial encoding. In this work, we resolve these challenges and show that it is possible to embed an arbitrary number of secrets in one encoding and propose gadgets that are secure against combined attacks. We present two constructions that are generic and significantly improve the computational and randomness complexity of existing compilers, such as the laOla compiler presented by Berndt et al. at CRYPTO'$23$ and its improvement by Arnold et al. For example, for an AES evaluation that protects against $t$ probes and $e$ faults, we improve the randomness complexity of the state-of-the-art construction when $t+e>3$, leading to an improvement of up to a factor of $2.41$.

We introduce ZODA, short for 'zero-overhead data availability,' which is a protocol for proving that symbols received from an encoding (for tensor codes) were correctly constructed. ZODA has optimal overhead for both the encoder and the samplers. Concretely, the ZODA scheme incurs essentially no incremental costs (in either computation or size) beyond those of the tensor encoding itself. In particular, we show that a slight modification to the encoding scheme for tensor codes allows sampled rows and columns of this modified encoding to become proofs of their own correctness. When used as part of a data availability sampling protocol, both encoders (who encode some data using a tensor code with some slight modifications) and samplers (who sample symbols from the purported encoding and verify that these samples are correctly encoded) incur no incremental communication costs and only small additional computational costs over having done the original tensor encoding. ZODA additionally requires no trusted setup and is plausibly post-quantum secure.

Suppose you have a supersingular $\ell$-isogeny graph with vertices given by $j$-invariants defined over $\mathbb{F}_{p^2}$, where $p = 4 \cdot f \cdot \ell^e - 1$ and $\ell \equiv 3 \pmod{4}$. We give an explicit parametrization of the maximal orders in $B_{p,\infty}$ appearing as endomorphism rings of the elliptic curves in this graph that are $\leq e$ steps away from a root vertex with $j$-invariant 1728. This is the first explicit parametrization of this kind and we believe it will be an aid in better understanding the structure of supersingular $\ell$-isogeny graphs that are widely used in cryptography. Our method makes use of the inherent directions in the supersingular isogeny graph induced via Bruhat-Tits trees, as studied in [1]. We also discuss how in future work other interesting use cases, such as $\ell=2$, could benefit from the same methodology.

The server-aided model for multiparty computation (MPC) was introduced to capture a real-world scenario where clients wish to off-load the heavy computation of MPC protocols to dedicated servers. A rich body of work has studied various trade-offs between security guarantees (e.g., semi-honest vs malicious), trust assumptions (e.g., the threshold on corrupted servers), and efficiency. However, all existing works make the assumption that all clients must agree on employing the same servers, and accept the same corruption threshold. In this paper, we challenge this assumption and introduce a new paradigm for server-aided MPC, where each client can choose their own set of servers and their own threshold of corrupted servers. In this new model, the privacy of each client is guaranteed as long as their own threshold is satisfied, regardless of the other servers/clients. We call this paradigm per-party private server-aided MPC to highlight both a security and efficiency guarantee: (1) per-party privacy, which means that each party gets their own privacy guarantees that depend on their own choice of the servers; (2) per-party complexity, which means that each party only needs to communicate with their chosen servers. Our primary contribution is a new theoretical framework for server-aided MPC. We provide two protocols to show feasibility, but leave it as a future work to investigate protocols that focus on concrete efficiency.

A central question in the theory of cryptography is whether we can build protocols that achieve stronger security guarantees, e.g., security against malicious adversaries, by combining building blocks that achieve much weaker security guarantees, e.g., security only against semi-honest adversaries; and with the minimal number of rounds. An additional focus is whether these building blocks can be used only as a black-box. Since Oblivious Transfer (OT) is the necessary and sufficient building block to securely realize any two-party (and multi-party) functionality, theoreticians often focus on proving whether maliciously secure OT can be built from a weaker notion of OT. There is a rich body of literature that provides (black-box) compilers that build malicious OT from OTs that achieve weaker security such as semi-malicious OT and defensibly secure OT, within the minimal number of rounds. However, no round-optimal compiler exists that builds malicious OT from the weakest notion of semi-honest OT, in the plain model. Correlation intractable hash (CIH) functions are special hash functions whose properties allow instantiating the celebrated Fiat-Shamir transform, and hence reduce the round complexity of public-coin proof systems. In this work, we devise the first round-optimal compiler from semi-honest OT to malicious OT, by a novel application of CIH for collapsing rounds in the plain model. We provide the following contributions. First, we provide a new CIH-based round-collapsing construction for general cut-and-choose. This gadget can be used generally to prove the correctness of the evaluation of a function. Then, we use our gadget to build the first round-optimal compiler from semi-honest OT to malicious OT. Our compiler uses the semi-honest OT protocol and the other building blocks in a black-box manner. However, for technical reasons, the underlying CIH construction requires the upper bound of the circuit size of the semi-honest OT protocol used. The need for this upper-bound makes our protocol not fully black-box, hence is incomparable with existing, fully black-box, compilers.

In this work, we address the problem of Delegated PSI (D-PSI), where a cloud server is introduced to handle most computational and communication tasks. D-PSI enables users to securely delegate their private sets to the cloud, ensuring the privacy of their data while allowing efficient computation of the intersection. The cloud operates under strict security requirements, learning nothing about the individual sets or the intersection result. Moreover, D-PSI minimizes user-to-user communication and supports "silent" processing, where the cloud can perform computations independently without user interaction, apart from set delegation and result retrieval. We formally define the D-PSI problem and propose a novel construction that extends beyond two-party scenarios to support multi-party settings. Our construction adheres to the D-PSI requirements, including security against semi-honest adversaries, and achieves computational and communication complexities close to the ideal "perfect" D-PSI protocol. Additionally, we demonstrate the practicality of our approach through a baseline implementation and an optimized version that further reduces computational overhead. Our results establish a strong foundation for secure and efficient PSI in real-world cloud computing scenarios.

In recent development of secure multi-party computation (MPC), pseudorandom correlations of subfield vector oblivious linear evaluation (sVOLE) type become popular due to their amazing applicability in multi-dimensional MPC protocols such as privacy-preserving biometric identification and privacy-preserving machine learning protocols. In this paper, we introduce a novel way of VOLE distribution in three-party and four-party honest majority settings with the aid of a trusted server. This new method significantly decreases the communication cost and the memory storage of random sVOLE instances. On the other hand, it also enables a streamline distribution process that can generate a sVOLE instance of an arbitrary length, which results in 100 percent of utility rate of random sVOLE in multi-dimensional MPC protocols while preserving complete precomputability.

Two most common ways to design non-interactive zero knowledge (NIZK) proofs are based on Sigma ($\Sigma$)-protocols (an efficient way to prove algebraic statements) and zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARK) protocols (an efficient way to prove arithmetic statements). However, in the applications of cryptocurrencies such as privacy-preserving credentials, privacy-preserving audits, and blockchain-based voting systems, the zk-SNARKs for general statements are usually implemented with encryption, commitment, or other algebraic cryptographic schemes. Moreover, zk-SNARKs for many different arithmetic statements may also be required to be implemented together. Clearly, a typical solution is to extend the zk-SNARK circuit to include the code for algebraic part. However, complex cryptographic operations in the algebraic algorithms will significantly increase the circuit size, which leads to impractically large proving time and CRS size. Thus, we need a flexible enough proof system for composite statements including both algebraic and arithmetic statements. Unfortunately, while the conjunction of zk-SNARKs is relatively natural and numerous effective solutions are currently available (e.g. by utilizing the commit-and-prove technique), the disjunction of zk-SNARKs is rarely discussed in detail. In this paper, we mainly focus on the disjunctive statements of Groth16, and we propose a Groth16 variant---CompGroth16, which provides a framework for Groth16 to prove the disjunctive statements that consist of a mix of algebraic and arithmetic components. Specifically, we could directly combine CompGroth16 with $\Sigma$-protocol or even CompGroth16 with CompGroth16 just like the logical composition of $\Sigma$-protocols. From this, we can gain many good properties, such as broader expression, better prover's efficiency and shorter CRS. In addition, for the combination of CompGroth16 and $\Sigma$-protocol, we also present two representative application scenarios to demonstrate the practicality of our construction.

In this paper we propose a constant time lattice reduction algorithm for integral dimension-4 lattices. Motivated by its application in the SQIsign post-quantum signature scheme, we provide for the first time a constant time LLL-like algorithm with guarantees on the length of the shortest output vector. We implemented our algorithm and ensured through various tools that it indeed operates in constant time. Our experiments suggest that in practice our implementation outputs a Minkowski reduced basis and thus can replace a non constant time lattice reduction subroutine in SQIsign.

In this work, we study cryptosystems that can be executed securely without fully trusting all machines, but only trusting the user's brain. This paper focuses on signature scheme. We first introduce a new concept called ``server-aided in-brain signature,'' which is a cryptographic protocol between a human brain and multiple servers to sign a message securely even if the user's device and servers are not completely trusted. Second, we propose a concrete scheme that is secure against mobile hackers in servers and malware infecting user's devices.

Functional Encryption (FE) is a powerful cryptographic primitive that allows for fine- grained computation over encrypted data. In the age of modern computing in complex environments, where data comes from multiple independent sources to be later jointly analysed in a fine-grained computation manner, the notion of multi-user functional encryption is becoming increasingly important. In particular, since their introduction (Goldwasser et al. at Eurocrypt’14; Chotard et al. at Asiacrypt’18), Multi-Client and Multi-Input FE become the subjects of a plethora of works, which study on concrete function classes, improving security, and more. Among many properties, one of the most important security property for Multi-Client/Multi-Input FE is the confidentiality of users’ encrypted data. Due to the complexity of these primitives, modeling a strong security notion and at the same time providing efficient constructions is a challenging task. However, all security notions considered so far for Multi-Client/Multi-Input FE are in the chosen- plaintext setting, whereas it is long settled that the chosen-ciphertext setting is the most relevant for practical security in classical public-key encryption. For FE, the only known works are on single-user context, namely by Benhamouda et al. (PKC’17), Gay (PKC’20), Castagnos et al. (TCS’22). This leaves open the questions, both conceptually and constructively, of attaining chosen-ciphertext security in the multi-user setting, notably for Multi-Client and Multi-Input FE. This work tackles the above questions of chosen-ciphertext security in multi-user context for FE for the first time: - We propose a new security notion for Multi-Client FE, and Multi-Input FE, in the chosen- ciphertext setting. Our notions extend the single-user notion that is studied in previous works and is robust against strong adversaries. - For the class computing inner products, we demonstrate the feasibility of our new notions by providing nouvel generic constructions for Multi-Client FE and Multi-Input FE. Surprisingly, our contruction for Multi-Input FE attains the same efficiency as in the public key single-client setting of previous works, and can be instantiated from the Decisional Diffie-Hellman or Decision Composite Residuosity assumptions. On the other hand, our contruction for Multi-Client FE enjoys an orignal toolkit of techniques that is developed to bootstrap a MCFE with chosen- plaintext security to chosen-ciphertext security, in its secret key setting, and can be instantiated from Symmetric eXternal Diffie-Hellman and Decision Linear assumptions.

Secret handshakes, introduced by Balfanz et al. [3], allow users associated with various groups to determine if they share a common affiliation. These protocols ensure crucial properties such as fairness (all participants learn the result simultaneously), affiliation privacy (failed handshakes reveal no affiliation information), and result-hiding (even participants within a shared group cannot infer outcomes of unrelated handshakes). Over time, various secret-handshake schemes have been proposed, with a notable advancement being the modular framework by Tsudik and Xu. Their approach integrates three key components: group signature schemes, centralized secure channels for each group, and decentralized group key-agreement protocols. Building upon this modularity, we propose significant updates. By addressing hidden complexities and revising the security model, we enhance both the efficiency and the privacy guarantees of the protocol. Specifically, we achieve the novel property of Self distinction—the ability to distinguish between two users in a session without revealing their identities—by replacing the group signature primitive with a new construct, the List MAC. This primitive is inherently untraceable, necessitating adjustments to the original syntax to support stronger privacy guarantees. Consequently, we introduce the Traitor Catching paradigm, where the transcript of a handshake reveals only the identity of a traitor, preserving the anonymity of all other participants. To showcase the flexibility and robustness of our updated framework, we present two post-quantum instantiations (a hash-based one and another based on lattices). Our approach not only corrects prior limitations but also establishes a new benchmark for privacy and security in secret handshakes.

Space networking has become an increasing area of development with the advent of commercial satellite networks such as those hosted by Starlink and Kuiper, and increased satellite and space presence by governments around the world. Yet, historically such network designs have not been made public, leading to limited formal cryptographic analysis of the security offered by them. One of the few public protocols used in space networking is the Bundle Protocol, which is secured by Bundle Protocol Security (BPSec), an Internet Engineering Task Force (IETF) standard. We undertake a first analysis of BPSec under its default security context, building a model of the secure channel security goals stated in the IETF standard, and note issues therein with message loss detection. We prove BPSec secure, and also provide a stronger construction, one that supports the Bundle Protocol's functionality goals while also ensuring destination awareness of missing message components.

Multi-input and large-precision lookup table (LUT) evaluation pose significant challenges in Fully Homomorphic Encryption (FHE). Currently, two modes are employed to address this issue. One is tree-based functional bootstrapping (TFBS), which uses multiple blind rotations to construct a tree for LUT evaluation. The second is circuit bootstrapping, which decomposes all inputs into bits and utilizes a CMux tree for LUT evaluation. In this work, we propose a novel mode that is leveled functional bootstrapping. This mode utilizes the external product tree to perform multi-input functional bootstrapping. We implement TFBS and LFBS within the OpenFHE library. The results demonstrate that our method outperforms TFBS in both computational efficiency and bootstrapping key size. Specifically, for 12-bit and 16-bit input LUTs, our method is approximately two to three orders of magnitude faster than TFBS. Finally, we introduce a novel scheme-switching framework that supports large-precision polynomial and non-polynomial evaluations. The framework leverages digital extraction techniques to enable seamless switching between the BFV and LFBS schemes.

In this paper, we introduce an oracle version of the Restricted Syndrome Decoding Problem (RSDP) and propose novel authentication protocols based on the hardness of this problem. They follow the basic structure of the HB-family of authentication protocols and later improvements but demonstrate several advantages. An appropriate choice of multiplicative subgroup and ring structure gives rise to a very efficient hardware implementation compared to other \emph{Learning Parity with Noise} based approaches. In addition, the new protocols also have lower key size, lower communication costs, and potentially better completeness/soundness compared to learning-based alternatives. This is appealing in the context of low-cost, low-powered authenticating devices such as radio frequency identification (RFID) systems. Lastly, we show that with additional assumptions, RSDP can be used to instantiate a Man-in-the-Middle secured authentication protocol.

Electromagnetic side-channel analysis is a powerful method for monitoring processor activity and compromising cryptographic systems in air-gapped environments. As analytical methodologies and target devices evolve, the importance of leakage localization and probe aiming becomes increasingly apparent for capturing only the desired signals with a high signal-to-noise ratio. Despite its importance, there remains substantial reliance on unreliable heuristic approaches and inefficient exhaustive searches. Furthermore, related studies often fall short in terms of feasibility, practicality, and performance, and are limited to controlled DUTs and low-end MCUs. To address the limitations and inefficiencies of the previous approaches, we propose a novel methodology―${\rm P{\tiny ROBE}S{\tiny HOOTER}}$―for leakage localization and probe aiming. This approach leverages new insights into the spatial characteristics of amplitude modulation and intermodulation distortion in processors. As a result, ${\rm P{\tiny ROBE}S{\tiny HOOTER}}$ provides substantial improvements in various aspects: $\boldsymbol 1)$ it is applicable to not only simple MCUs but also complex SoCs, $\boldsymbol 2)$ it effectively handles multi-core systems and dynamic frequency scaling, $\boldsymbol 3)$ it is adoptable to uncontrollable DUTs, making it viable for constrained real-world attacks, and $\boldsymbol 4)$ it performs significantly faster than previous methods. To demonstrate this, we experimentally evaluate ${\rm P{\tiny ROBE}S{\tiny HOOTER}}$ on a high-end MCU (the NXP i.MX RT1061 featuring a single ARM Cortex-M7 core) and a complex SoC (the Broadcom BCM2711 equipped with the Raspberry Pi 4 Model B, featuring four ARM Cortex-A72 cores).

Today, many auctions are carried out with the help of intermediary platforms like Google and eBay. These platforms serve as a rendezvous point for the buyers and sellers, and charge a fee for its service. We refer to such auctions as platform-assisted auctions. Traditionally, the auction theory literature mainly focuses on designing auctions that incentivize the buyers to bid truthfully, assuming that the platform always faithfully implements the auction. In practice, however, the platforms have been found to manipulate the auctions to earn more profit, resulting in high-profile anti-trust lawsuits. We propose a new model for studying platform-assisted auctions in the permissionless setting, where anyone can register and participate in the auction. We explore whether it is possible to design a dream auction in this new model, such that honest behavior is the utility-maximizing strategy for each individual buyer, the platform, the seller, as well as platform-seller or platform-buyer coalitions. Through a collection of feasibility and infeasibility results, we carefully characterize the mathematical landscape of platform-assisted auctions. Interestingly, our work reveals exciting connections between cryptography and mechanism design. We show how cryptography can lend to the design of an efficient platform-assisted auction with dream properties. Although a line of works have also used multi-party computation (MPC) or the blockchain to remove the reliance on a trusted auctioneer, our work is distinct in nature in several dimensions. First, we initiate a systematic exploration of the game theoretic implications when the service providers (e.g., nodes that implement the MPC or blockchain protocol) are strategic and can collude with sellers or buyers. Second, we observe that the full simulation paradigm used in the standard MPC literature is too stringent and leads to high asymptotical costs. Specifically, because every player has a different private outcome in an auction protocol, to the best of our knowledge, running any generic MPC protocol among the players would incur at least $n^2$ total cost where $n$ is the number of buyers.We propose a new notion of simulation called {\it utility-dominated emulation} that is sufficient for guaranteeing the game-theoretic properties needed in an auction. Under this new notion of simulation, we show how to design efficient auction protocols with quasilinear efficiency, which gives an $n$-fold improvement over any generic approach.

Cryptography based on the presumed hardness of decoding codes -- i.e., code-based cryptography -- has recently seen increased interest due to its plausible security against quantum attackers. Notably, of the four proposals for the NIST post-quantum standardization process that were advanced to their fourth round for further review, two were code-based. The most efficient proposals -- including HQC and BIKE, the NIST submissions alluded to above -- in fact rely on the presumed hardness of decoding structured codes. Of particular relevance to our work, HQC is based on quasi-cyclic codes, which are codes generated by matrices consisting of two cyclic blocks. In particular, the security analysis of HQC requires a precise understanding of the Decryption Failure Rate (DFR), whose analysis relies on the following heuristic: given random "sparse" vectors $e_1,e_2$ (say, each coordinate is i.i.d. Bernoulli) multiplied by fixed "sparse" quasi-cyclic matrices $A_1,A_2$, the weight of resulting vector $e_1A_1+e_2A_2$ is very concentrated around its expectation. In the documentation, the authors model the distribution of $e_1A_1+e_2A_2$ as a vector with independent coordinates (and correct marginal distribution). However, we uncover cases where this modeling fails. While this does not invalidate the (empirically verified) heuristic that the weight of $e_1A_1+e_2A_2$ is concentrated, it does suggest that the behavior of the noise is a bit more subtle than previously predicted. Lastly, we also discuss implications of our result for potential worst-case to average-case reductions for quasi-cyclic codes.

This paper improves upon the quantum circuits required for the Shor's attack on binary elliptic curves. We present two types of quantum point addition, taking both qubit count and circuit depth into consideration. In summary, we propose an in-place point addition that improves upon the work of Banegas et al. from CHES'21, reducing the qubit count – depth product by more than $73\%$ – $81\%$ depending on the variant. Furthermore, we develop an out-of-place point addition by using additional qubits. This method achieves the lowest circuit depth and offers an improvement of over $92\%$ in the qubit count – quantum depth product (for a single step). To the best of our knowledge, our work improves from all previous works (including the CHES'21 paper by Banegas et al., the IEEE Access'22 paper by Putranto et al., and the CT-RSA'23 paper by Taguchi and Takayasu) in terms of circuit depth and qubit count – depth product. Equipped with the implementations, we discuss the post-quantum security of the binary elliptic curve cryptography. Under the MAXDEPTH metric (proposed by the US government's NIST), the quantum circuit with the highest depth in our work is $2^{24}$, which is significantly lower than the MAXDEPTH limit of $2^{40}$. For the gate count – full depth product, a metric for estimating quantum attack cost (proposed by NIST), the highest complexity in our work is $2^{60}$ for the curve having degree 571 (which is comparable to AES-256 in terms of classical security), considerably below the post-quantum security level 1 threshold (of the order of $2^{156}$).

Internet-scale consensus protocols used by blockchains are designed to remain operational in the presence of unexpected temporary crash faults (the so-called sleepy model of consensus) -- a critical feature for the latency-sensitive financial applications running on these systems. However, their leader-based architecture, where a single block proposer is responsible for creating the block at each height, makes them vulnerable to short-term censorship attacks, in which the proposers profit at the application layer by excluding certain transactions. In this work, we introduce an atomic broadcast protocol, secure in the sleepy model, that ensures the inclusion of all transactions within a constant expected time, provided that at least one participating node is non-censoring at all times. Unlike traditional approaches, our protocol avoids designating a single proposer per block height, instead leveraging a so-called dynamically available common subset (DACS) protocol -- the first of its kind in the sleepy model. Additionally, our construction guarantees deterministic synchronization -- once an honest node confirms a block, all other honest nodes do so within a constant time, thus addressing a shortcoming of many low-latency sleepy protocols.

Index Calculus (IC) algorithm is the most effective probabilistic algorithm for solving discrete logarithms over finite fields of prime numbers, and it has been widely applied to cryptosystems based on elliptic curves. Since the IC algorithm was proposed in 1920, the research on it has never stopped, especially discretization of prime numbers on the finite fields, both the algorithm itself and its application have been greatly developed. Of course, there has been some research on elliptic curves,but with little success. For the IC algorithm, scholars pay more attention to how to improve the probability of solving and reduce the time complexity of calculation. It is the first time for the IICA to study the optimization problem of the IC by using the method of integer. However, the IICA only studies the case of integer up, and fails to consider the case of integer down. It is found that the integer direction of the IICA can be integer up or integer down, but the concept of modular multiplication needs to be used when integer down. After optimizing the IICA, the probability of successful solution of discrete logarithm is increased by nearly 2 times, and the number of transformations is also reduced to a certain extent, thus reducing the time complexity of solution. The re-optimized the IC algorithm greatly improves the probability of successful the IC solution. This research result poses a serious challenge to cryptosystems based on finite fields of prime numbers.

The Performance Monitoring Unit (PMU), a standard feature in all modern computing systems, presents significant security risks by leaking sensitive user activities through microarchitectural event data. This work demonstrates the feasibility of remote side-channel attacks leveraging PMU data, revealing vulnerabilities that compromise user privacy and enable covert surveillance without physical access to the target machine. By analyzing the PMU feature space, we create distinct micro-architectural fingerprints for benchmark applications, which are then utilized in machine learning (ML) models to detect the corresponding benchmarks. This approach allows us to build a pre-trained model for benchmark detection using the unique micro-architectural fingerprints derived from PMU data. Subsequently, when an attacker remotely accesses the victim’s PMU data, the pre-trained model enables the identification of applications used by the victim with high accuracy. In our proof-of-concept demonstration, the pre-trained model successfully identifies applications used by a victim when the attacker remotely accesses PMU data, showcasing the potential for malicious exploitation of PMU data. We analyze stress-ng benchmarks and build our classifiers using logistic regression, decision tree, k-nearest neighbors, and random forest ML models. Our proposed models achieve an average prediction accuracy of 98%, underscoring the potential risks associated with remote side-channel analysis using PMU data and emphasizing the need for more robust safeguards. This work underscores the urgent need for robust countermeasures to protect against such vulnerabilities and provides a foundation for future research in micro-architectural security.

This paper introduces new protocols for secure multiparty computation (MPC) leveraging Discrete Wavelet Transforms (DWTs) for computing nonlinear functions over large domains. By employing DWTs, the protocols significantly reduce the overhead typically associated with Lookup Table-style (LUT) evaluations in MPC. We state and prove foundational results for DWT-compressed LUTs in MPC, present protocols for 9 of the most common activation functions used in ML, and experimentally evaluate the performance of our protocols for large domain sizes in the LAN and WAN settings. Our protocols are extremely fast -- for instance, when considering 64-bit inputs, computing 1000 parallel instances of the sigmoid function, with an error less than $2^{-24}$ takes only a few hundred milliseconds incurs just 29\,KiB of online communication (40 bytes per evaluation).

This paper presents a novel approach to calculating the Levenshtein (edit) distance within the framework of Fully Homomorphic Encryption (FHE), specifically targeting third-generation schemes like TFHE. Edit distance computations are essential in applications across finance and genomics, such as DNA sequence alignment. We introduce an optimised algorithm that significantly reduces the cost of edit distance calculations called Leuvenshtein. This algorithm specifically reduces the number of programmable bootstraps (PBS) needed per cell of the calculation, lowering it from approximately 94 operations -- required by the conventional Wagner-Fisher algorithm -- to just 1. Additionally, we propose an efficient method for performing equality checks on characters, reducing ASCII character comparisons to only 2 PBS operations. Finally, we explore the potential for further performance improvements by utilising preprocessing when one of the input strings is unencrypted. Our Leuvenshtein achieves up to $278\times$ faster performance compared to the best available TFHE implementation and up to $39\times$ faster than an optimised implementation of the Wagner-Fisher algorithm. Moreover, when offline preprocessing is possible due to the presence of one unencrypted input on the server side, an additional $3\times$ speedup can be achieved.

Side-channel analysis (SCA) does not aim at the algorithm's weaknesses but rather its implementations. The rise of machine learning (ML) and deep learning (DL) is giving adversaries advanced capabilities to perform stealthy attacks. In this paper, we propose DL-SCADS, a DL-based approach along with signal decomposition techniques to leverage the power of secret key extraction from post-silicon EM/power side-channel traces. We integrate previously proven effective ideas of model ensembling and automated hyperparameter tuning with signal decomposition to develop an efficient and robust side-channel attack. Extensive experiments are performed on Advanced Encryption Standard (AES) and Post-Quantum Cryptography (PQC) to demonstrate the efficacy of our approach. The evaluation of the performance of the side-channel attack employing various decomposition techniques and comparison with the proposed approach in a range of datasets are also tabulated.

This article explores the potential of Secret Sharing-Based Internet of Things (SBIoT) as a promising cryptographic element across diverse applications, including secure data storage in commercial cloud systems (Datachest), smart home environments (encompassing sensors, cameras, smart locks, and smart assistants), and e-health applications (protecting patient data and medical records). Beyond these applications, the paper makes two key contributions: the introduction of a novel cheater identification algorithm designed to verify the correct submission of shares during secret reconstruction, and empirical validation through experimental studies to support the theoretical advancements. This multifaceted approach not only demonstrates the versatility of SBIoT but also proposes innovative mechanisms to enhance security and integrity, contributing to the development of a more robust cryptographic framework. This article expands upon the work presented in the poster "A Combinatorial Approach to IoT Data Security" at IWSEC 2023, Yokohama, Japan.

Side-channel attacks (SCA) pose a significant threat to cryptographic implementations, including those designed to withstand the computational power of quantum computers. This paper introduces the first side-channel attack on an industry-grade post-quantum cryptography implementation. Specifically, we present a Correlation Power Analysis (CPA) attack targeting the open-source hardware implementation of ML-DSA within a Silicon Root of Trust framework developed through a multi-party collaboration involving leading technology companies. Our attack focuses on the modular reduction process that follows the Number Theoretic Transform-based polynomial pointwise multiplication. By exploiting side-channel leakage from a distinctive unique reduction algorithm and leveraging the zeroization mechanism used to securely erase sensitive information by clearing internal registers, we significantly enhance the attack's efficacy. Our findings reveal that an adversary can extract the secret keys using only 10,000 power traces. With access to these keys, an attacker could forge signatures for certificate generation, thereby compromising the integrity of the root of trust. This work highlights the vulnerabilities of industry-standard root-of-trust systems to side-channel attacks. It underscores the urgent need for robust countermeasures to secure commercially deployed systems against such threats.

This survey provides a comprehensive examination of verifiable computing, tracing its evolution from foundational complexity theory to modern zero-knowledge succinct non-interactive arguments of knowledge (ZK-SNARKs). We explore key developments in interactive proof systems, knowledge complexity, and the application of low-degree polynomials in error detection and verification protocols. The survey delves into essential mathematical frameworks such as the Cook-Levin Theorem, the sum-check protocol, and the GKR protocol, highlighting their roles in enhancing verification efficiency and soundness. By systematically addressing the limitations of traditional NP-based proof systems and then introducing advanced interactive proof mechanisms to overcome them, this work offers an accessible step-by-step introduction for newcomers while providing detailed mathematical analyses for researchers. Ultimately, we synthesize these concepts to elucidate the GKR protocol, which serves as a foundation for contemporary verifiable computing models. This survey not only reviews the historical and theoretical advancements in verifiable computing over the past three decades but also lays the groundwork for understanding recent innovations in the field.

In [Pan21] a linearization attack is proposed in order to break the cryp- tosystem proposed in [Gli21]. We want to propose here a non-linearizable operator that disables this attack as this operator doesn't give raise to a quasigrup and doesn't obey the latin square property.

Distributed key generation (DKG) is a Byzantine fault tolerant protocol among a set of $n$ parties that enables generation of a public-secret key pair for threshold cryptosystems without a trusted third party. It serves as a building block for many decentralized protocols, such as randomness beacons, threshold encryption and signing, consensus, and general multi-party computation. Of particular importance are asynchronous DKG protocols with low communication and round complexity. However, all existing constructions for asynchronous DKG require cubic or higher communication costs in the number of parties (including setup costs) to terminate. This severely limits their practicality, especially in large-scale systems such as the internet or blockchains, where communication and round complexity are the main bottlenecks to efficiency. In this paper, we present the first asynchronous DKG protocol that overcomes this limitation. Our protocol has the following desirable properties. It is resilient to a strongly adaptive adversary that can corrupt up to $f < n/3$ parties. Parameterized by a natural number $1 \leq k \leq \log{n}$, it has an expected communication cost of $O(\lambda^2 n^{2+1/k})$ bits and terminates in expected $O(k)$ rounds, where $\lambda$ denotes the security parameter. Furthermore, for setup, it requires a plain public key infrastructure (PKI) and random oracles, which is standard in the literature on DKG protocols. From a conceptual perspective, our main contribution is to adapt the classical recursive paradigm (for distributed protocols) from the synchronous to the asynchronous model and to apply it to asynchronous DKG.

Cryptocurrency practices worldwide are seen as innovative, yet they navigate a fragmented regulatory environment. Many local authorities aim to balance promoting innovation, safeguarding consumers, and managing potential threats. In particular, it is unclear how people deal with cryptocurrencies in the regions where trading or mining is prohibited. This insight is crucial in conveying the risk reduction strategies. To address this, we conducted semi-structured interviews with 28 cryptocurrency traders and miners from Bangladesh, where the local authority is hostile towards cryptocurrencies. Our research revealed that the participants use unique strategies to mitigate risks around cryptocurrencies. Our findings indicate a prevalent uncertainty at both personal and organizational levels concerning the interpretation of laws, a situation worsened by the actions of the major financial service providers who indirectly facilitate cryptocurrency transactions. We further connect our findings to the broader issues in HCI regarding folk models, informal market and legality, and education and awareness.

Secure multi-party computation (MPC) is a crucial tool for privacy-preserving computation, but it is getting increasingly complicated due to recent advancements and optimizations. Programming tools for MPC allow programmers to develop MPC applications without mastering all cryptography. However, most existing MPC programming tools fail to attract real users due to the lack of documentation, maintenance, and the ability to compose with legacy codebases. In this work, we build Smaug, a modular extension of LLVM. Smaug seamlessly brings all LLVM support to MPC programmers, including error messaging, documentation, code optimization, and frontend support to compile from various languages to LLVM intermediate representation (IR). Smaug can efficiently convert non-oblivious LLVM IR to their oblivious counterparts while applying popular optimizations as LLVM code transformations. With benchmarks written in C++ and Rust and backends for Yao and GMW protocols, we observe that Smaug performs as well as (and sometimes much better than) prior tools using domain-specific languages with similar backends. Finally, we use Smaug to compile open-source projects that implement Minesweeper and Blackjack, producing usable two-party games with ease.

In classical DNSSEC, a drop-in replacement with quantum-safe cryptography would increase DNS query resolution times by $\textit{at least}$ a factor of $2\times$. Since a DNS response containing large post-quantum signatures is likely to get marked truncated ($\texttt{TC}$) by a nameserver (resulting in a wasted UDP round-trip), the client (here, the resolver) would have to retry its query over TCP, further incurring a $\textit{minimum}$ of two round-trips due to the three-way TCP handshake. We present $\mathsf{TurboDNS}$: a backward-compatible protocol that eliminates $\textit{two}$ round-trips from the preceding flow by 1) sending TCP handshake data in the initial DNS/UDP flight itself, and 2) immediately streaming the DNS response over TCP after authenticating the client with a cryptographic cookie. Our experiments show that DNSSEC over $\mathsf{TurboDNS}$, with either Falcon-512 or Dilithium-2 as the zone signing algorithm, is practically as fast as the currently deployed ECDSA P-256 and RSA-2048 setups in resolving $\texttt{QTYPE}$ $\texttt{A}$ DNS queries.

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 provide the first attribute based encryption (ABE) scheme for Turing machines supporting unbounded collusions from lattice assumptions. In more detail, the encryptor encodes an attribute $\mathbf{x}$ together with a bound $t$ on the machine running time and a message $m$ into the ciphertext, the key generator embeds a Turing machine $M$ into the secret key and decryption returns $m$ if and only if $M(\mathbf{x})=1$. Crucially, the input $\mathbf{x}$ and machine $M$ can be of unbounded size, the time bound $t$ can be chosen dynamically for each input and decryption runs in input specific time. Previously the best known ABE for uniform computation supported only non-deterministic log space Turing machines (${\sf NL})$ from pairings (Lin and Luo, Eurocrypt 2020). In the post-quantum regime, the state of the art supports non-deterministic finite automata from LWE in the $\textit{ symmetric}$ key setting (Agrawal, Maitra and Yamada, Crypto 2019). In more detail, our results are: 1. We construct the first ABE for ${\sf NL}$ from the LWE, evasive LWE (Wee, Eurocrypt 2022 and Tsabary, Crypto 2022) and Tensor LWE (Wee, Eurocrypt 2022) assumptions. This yields the first (conjectured) post-quantum ABE for ${\sf NL}$. 2. Relying on LWE, evasive LWE and a new assumption called $\textit{circular tensor}$ LWE, we construct ABE for all Turing machines. At a high level, the circular tensor LWE assumption incorporates circularity into the tensor LWE (Wee, Eurocrypt 2022) assumption. Towards our ABE for Turing machines, we obtain the first CP-ABE for circuits of unbounded depth and size from the same assumptions -- this may be of independent interest.