International Association
for Cryptologic Research

The QC-MDPC McEliece cryptosystem is a promising candidate for post-quantum cryptography, and the decoding performance of the underlying QC-MDPC code directly affects the security of the scheme. Deep unfolding, a framework that unfolds an iterative algorithm into a neural network with trainable weights, has been shown to improve belief propagation (BP) decoding for codes with dense parity-check matrices. However, applying deep unfolding directly to the large QC-MDPC codes used in practice is impractical owing to the computational cost of training. Moreover, in QC-MDPC-based cryptosystems, the parity-check matrix serves as the secret key and must be replaced periodically; key-specific training would therefore need to be repeated at each replacement. We address both issues through zero-shot transfer. We propose weight homogenisation, which constrains the trainable weights to a single scalar per iteration, making them independent of the specific Tanner graph. This enables a decoder trained on a small QC-MDPC code to be applied directly to larger codes. Experiments on QC-MDPC codes with parameters proposed for 80-bit and 128-bit security demonstrate that the proposed method achieves a lower decoding error rate than standard BP.

In side-channel analysis of ML-KEM (a NIST-standard PQC algorithm), SASCA is a powerful profiling attack. However, obtaining a profiling device strictly matching the target is challenging in practice. To address this, we propose the first profiling-device-free SASCA framework for ML-KEM. The framework first controls the NTT input by choosing ciphertexts and trains a leakage model. Subsequently, leveraging the similarity between NTT and INTT, it uses adversarial unsupervised domain adaptation to fine-tune the model for INTT and recover its secret input. Validated on real embedded devices, the framework achieves effective key recovery using a comparable number of traces to profiling SASCA.

A key-independent secret-key distinguisher identifies structural deviations from an ideal random permutation without discovering any information about the secret key. It is therefore of primary importance for understanding the inherent properties of a block cipher's round function. While numerous key-independent secret-key distinguishers have been proposed for 5- and 6-round AES, none has been proposed for 7-round AES to date. In this paper, we propose the first key-independent secret-key distinguisher for 7-round AES, which exploits solely the structural properties of the round function. We propose the Joint Generalized Zero-Difference Property, where a quartet constructed from related differences satisfies three distinct generalized zero-difference properties simultaneously. By leveraging this joint property, we construct a new 7-round differential characteristic that a right quartet follows with a probability of $2^{-250.4}$, whereas a random permutation satisfies the same conditions with a probability of $2^{-253.4}$. Based on this characteristic, we design a distinguishing attack requiring data, time, and memory complexities of $2^{126.2}$. Our analysis confirms that the proposed distinguisher achieves a success probability of approximately 77.8%. We experimentally verify the joint property using small-scale AES, confirming that the theoretical predictions match the observed results. This work achieves the longest-round key-independent secret-key distinguisher for AES reported to date.

Event date: 24 May to 28 May 2027

Event date: 19 May 2026

Event date: 9 October to 10 October 2026
Submission deadline: 19 June 2026
Notification: 21 August 2026

In this work, we revisit the dual attack framework proposed by Pouly and Shen, focusing on the lattice Gaussian sampling term that is a significant bottleneck in the overall attack complexity. We show that this sampling step can be quantumly accelerated by combining the lower bound underlying Wang and Ling's analysis of Klein's algorithm with the quantum rejection sampling (QRS) framework proposed by Ozols et al. Specifically, this lower bound gives precisely the pointwise condition required for quantum rejection sampling when given coherent oracle access to a truncated Klein proposal distribution, which yields a quantum procedure for preparing the truncated dual $q$-ary lattice Gaussian with a quadratic reduction in the sampling complexity. The truncation radius is chosen so that the truncated distribution is negligibly close to the full lattice Gaussian in total variation distance. Substituting this sampler into their dual attack framework results in reduced overall attack-cost estimates. Compared with the Pouly and Shen dual attack (no modulus switching), our method reduces the estimated attack cost by $9$, $4$, and $13$ bits for Kyber-512, Kyber-768, and Kyber-1024 respectively.

TLA$^+$ (Temporal Logic of Actions) is a formal specification language well-suited for distributed systems. However, writing proper TLA$^+$ scripts requires high domain expertise. When it comes to modeling Byzantine behaviors for Byzantine fault-tolerant consensus protocols, the simulation of malicious behavior is a fundamental challenge: overly simplified modeling misses critical vulnerabilities, and verbose modeling leads to state-space explosion.

In this paper, we present TLAssist, a large language model (LLM)-assisted tool for semi-automated TLA$^+$ generation tailored for Byzantine reliable broadcast (RBC) protocols. We provide a highly structured workflow and domain-specific data format to improve the quality of LLM prompts. Using five RBC protocols as case studies, we have some interesting findings. First, the specification generated by TLAssist outperforms many open-source TLA$^+$ scripts we are aware of, including those written by domain experts. Second, TLAssist can assist domain experts in identifying deep design flaws. Notably, our case study on the (2,3,4)-Optimistic RBC (a CCS'25 distinguished paper) captures a subtle issue that causes the violation of the totality property. Finally, TLAssist is useful for non-experts. Namely, we show that by revising the protocols slightly, the generated error traces effectively show complex corner cases that can facilitate understanding of the design.

Cloud computing has become the standard for large-scale computation, offering elastic scalability and on-demand resources that exceed typical on-premise capabilities. However, many large-scale computations over sensitive data -- such as genome-wide association studies (GWAS) -- face significant barriers to cloud adoption due to privacy concerns and regulatory constraints. While cryptographic primitives like multi-party computation can alleviate these concerns through provable privacy guaranties, their substantial communication and computational overhead can make cloud deployment cost-prohibitive. To address both privacy and cost constraints, we present ThriftyMPC. ThriftyMPC is a framework that leverages spot instances (ephemeral cloud compute at reduced rates) to enable cost-effective, privacy-preserving computation at scale by combining secure multi-party computation with preemption-tolerant execution. We introduce a formal model for multi-party execution under ephemeral compute conditions, demonstrate how ThriftyMPC handles spot instance preemptions while maintaining cryptographic security guaranties, and provide a formal discussion of these guaranties. Our evaluations on realistic GWAS-inspired workloads over the Google Cloud Platform demonstrate robust execution despite spot instance churn, and show significant cost reduction compared to the state-of-the-art multi-party computation framework (MP-SPDZ) run traditionally using on-demand instances. We show that leveraging multi-party computation on spot instances makes privacy-preserving computation economically viable, enabling organizations to harness the cloud for sensitive workloads previously confined to isolated, on-premise deployments.

Threshold ECDSA signing has become a standard building block for securing cryptocurrency assets, with the protocol of Doerner, Kondi, Lee, and shelat (DKLs, IEEE S&P 2024) emerging as a leading solution due to its efficiency and widespread industry adoption.

In this work, we revisit the DKLs protocol to evaluate its concrete security and implementation trade-offs:

* Vector Oblivious Linear Evaluation (VOLE): We identify subtle issues in the underlying OT-based Vector Oblivious Linear Evaluation (VOLE) sub-protocol, showing that original parameter choices must be adjusted to reach intended security levels. To address this, we provide a complete analysis of three VOLE variants offering different trade-offs between bandwidth and round complexity.

* Two-Party Signing: We introduce an optimized two-party signing protocol that shifts the majority of computation and communication to a message- and key-independent preprocessing phase. This results in an exceptionally efficient online phase where each party exchanges only 0.2KB, a roughly 600 times reduction in communication compared to the full protocol, without being susceptible to known ``pre-signature'' attacks.

Our findings consolidate the security of the protocol while providing significant efficiency improvements for practical deployment and standardization.

Bootstrapping is the key technique that turns leveled homomorphic encryptionc into fully homomorphic encryption, but it remains a major efficiency bottleneck. Recent work by Z. Liu and Y. Wang (ASIACRYPT 2023) showed how to bootstrap \(N\) LWE ciphertexts with total cost of \(\widetilde{O}(N)\) polynomial multiplications based on the BFV scheme. However, their results achieve \(\widetilde{O}(1)\) complexity only through amortization over large batches, and do not give a genuine non-amortized \(\widetilde{O}(1)\) bound for a single ciphertext. In this paper, we present a BFV-based functional bootstrapping algorithm for arbitrary functions over large plaintext spaces with total cost of \(\widetilde{O}(1)\) polynomial multiplications for one LWE ciphertext. The same construction also supports small and moderate batches, and processes a batch of \(m\) ciphertexts with total cost \(\widetilde{O}(m)\) in the supported parameter range. The main technical ingredient is a sparse-packing polynomial-evaluation method for BFV ciphertexts, which exploits the duplicated-slot structure to evaluate an arbitrary polynomial on \(m\) encrypted inputs with total cost of \(\widetilde{O}(m)\). We implement the scheme in Lattigo using the BFV scheme. At 128 bit security and on a single thread, bootstrapping an arbitrary function takes 3.15 seconds for one ciphertext encrypting a 9-bit plaintext and 3.77 seconds for 128 such ciphertexts in one batched invocation. For 16-bit plaintexts, it takes 10.63 seconds for one ciphertext and 18.07 seconds for 16 ciphertexts. These results show that non-amortized single-ciphertext functional bootstrapping, as well as small and moderate batch bootstrapping, can be practical for arbitrary functions over relatively large plaintext spaces.

Threshold ring signatures (TRS) enable a quorum of $T$ users to jointly sign a message while hiding which $T$ of the $N$ ring members participated, supporting privacy-preserving endorsement in ad-hoc settings. That said, many deployments do not need anonymity over every $T$-subset of a ring: when the approval pattern is already public, a structured ring can be sufficient. In this work, we first formalize this setting as a structured threshold ring signature (sTRS) and introduce $\mathsf{LoTRS}$, a lattice-based sTRS that avoids a dedicated leader and keeps interaction to the optimal number of two rounds by separating the threshold signing relation from the anonymity mechanism. To the best of our knowledge, $\mathsf{LoTRS}$ is the first construction in which a TRS variant is obtained by combining: (i) an aggregated signing layer: a two-round lattice-based multisignature protocol producing an aggregated signature relation, with (ii) a selection-hiding layer: a $1$-out-of-$N$ proof that hides the chosen ring element supporting that relation. While it is natural to use a $T$-out-of-$N$ proof to build a TRS, our $\mathsf{LoTRS}$ exploits a $1$-out-of-$N$ proof to significantly improve efficiency. $\mathsf{LoTRS}$ concretely instantiates the aggregated signing layer using $\mathsf{DualMS}$ (Crypto'23) and the selection-hiding layer arising from Esgin et al.'s lattice-based one-out-of-many proof (IEEE S&P'22).

Our $(T, N\!\cdot\!T)$-$\mathsf{LoTRS}$ construction achieves $\mathsf{polylog}(N, T)$ signature size and outperforms $(T, N)$-TRS schemes significantly. For example, for $N=100$ and $T=50$, our signature size is only $36$ KB, which is $\approx3.5 \times$ smaller than the previously best performing lattice-based scheme $\mathsf{LastRings}$ by Jeon et al (ISC'25). Our Rust reference implementation further supports practicality: for $T=16$ and $N=32$, i.e., structured ring size $T\cdot N = 512$, it produces $25$ KB signatures, with mean signing time $149$ ms and verification time $43$ ms in a release build on a Ryzen AI 9 HX 370 laptop.

We study $t$-out-of-$n$ threshold fully homomorphic encryption (ThFHE) based on Shamir secret sharing (SSS) in the asynchronous setting. A central bottleneck for SSS-based ThFHE is that Lagrange reconstruction during distributed decryption can amplify noise, forcing a substantially larger ciphertext modulus to maintain correctness.

In this work, we revisit SSS-based ThFHE and give a rigorous analysis of the correctness and simulation-security constraints that govern parameter choices. We then compare families of Lagrange interpolation points through the lens of these constraints.

Our main contributions are analytic bounds that closely track empirical behavior and significantly reduce the modulus overhead required for distributed decryption. For example, for $n = 512$, our analysis reduces this modulus overhead (in bits) by 30% for $t = n/2$ and by up to 90% for $t$ close to $n$, compared to prior parameterizations.

Enhanced Gabidulin Matrix Codes (EGMC), introduced by Aragon, Couvreur, Dyseryn, Gaborit, and Vincotte at Asiacrypt 2024, were designed to hide the algebraic structure of Gabidulin matrix codes while enabling very compact McEliece- and Niederreiter-type encryption schemes, with ciphertexts as small as 65 bytes at the claimed 128-bit security level. Their security relies on the assumption that a masked EGMC code is hard to distinguish from a random matrix code. We show that this enhanced construction leaves enough structure for an equivalent code of the secret key to be recovered. Unlike previous cryptanalysis, our attack combines combinatorial and algebraic techniques to recover a Gabidulin-equivalent compressed code. This code can then be extended to a full-length equivalent secret key in polynomial time. As a result, the attack provides both a distinguisher and a key-recovery attack against the EGMC encryption schemes. The attack breaks all 16 proposed EGMC parameter sets by large margins. For example, for the claimed 128-bit parameter set $(2,17,37,4,0)$, it reduces the security level from 186 bits to 35 bits. In our implementation, the equivalent secret key is recovered in less than 10 minutes.

Polynomial multiplication is fundamental in lattice-based cryptography. While the Number Theoretic Transform (NTT) enables fast multiplication, it imposes constraints on the modulus of the coefficient field. Hafiz et al.\ (2025) addressed this limitation by analyzing the incomplete NTT, which combines a truncated NTT with conventional multiplication methods.

In this work, we revisit Toom-4 multiplication in the context of incomplete NTT. Although Toom-4 is asymptotically faster than Karatsuba, its precise cost has not been expressed in a form compatible with the incomplete NTT framework.

We present a concrete Toom-4 implementation and derive explicit operation counts that separate additions/subtractions and multiplications over the coefficient field. Our analysis based on addition chains yields a simple cost model for incomplete NTT.

Using this model, we analyze hybrid strategies combining Toom-4, Karatsuba, and incomplete NTT. We identify parameter ranges where Toom-4 is advantageous and validate the predicted behavior experimentally.

Du et al. (Security and Communication Networks, 2022) proposed a public-key authenticated searchable encryption scheme that employs Bloom filters and blockchain. In their scheme, Bloom filters are used to search encrypted keywords, while blockchain is used to ensure the integrity of search results that guarantees the search result is correct. In this paper, we demonstrate that Du et al.'s scheme leaks keyword information from ciphertexts. Our analysis focuses on the fact that the Bloom filter is uniquely determined by the keyword to be encrypted and is directly embedded in each ciphertext. We show that the proposed attack succeeds with the probability that no false positives occur in the Bloom filter, and we evaluate the false-positive probability to confirm that the attack achieves a sufficiently high success rate. Furthermore, we examine Du et al.'s security model and their assumed usage scenarios, and we discuss the validity of our attack under those conditions. We also consider a simple modification intended to prevent our attack and demonstrate that our attack, with a slight adaptation, remains effective against the modified scheme. In addition, we show that even when the search results differ, previously generated ciphertexts can still pass verification, indicating that the integrity verification mechanism based on blockchain is insufficient.

Unbiased and unpredictable randomness is a cornerstone of Web3 security, underpinning everything from consensus protocols to DeFi logic. Although Distributed Verifiable Random Functions (DVRFs) eliminate central points of failure, current designs often have to compromise performance. Most existing protocols are hindered by one of three limitations: proofs that scale linearly with the number of participants, high computational cost of bilinear pairings, or latency introduced by mandatory interactive steps during generation. In this work, we present Icy-DVRF, a protocol that improves DVRFwCP by employing a preprocessing scheme similar to FROST to reduce the number of interaction rounds among participants, by lowering the additional communication cost from $O(n^2 t)$ to $O(t)$ while maintaining constant-size proofs. The downside of our construction is that, relative to DDH-DVRF and GLOW-DVRF, this approach incurs an additional off-chain communication round due to the threshold structure of our non-interactive zero-knowledge proof. This architecture ensures that verification costs remain low, regardless of the set of participants. We evaluate Icy-DVRF against established standards and demonstrate that our protocol achieves a substantial efficiency gain over pairing-based alternatives. While theoretical estimates suggest verification costs of approximately one quarter of those of standard designs, our empirical benchmarks on the Sepolia testnet, utilizing the EIP-2537: Precompile for BLS12-381 curve operations, confirm that Icy-DVRF requires only 88,803 gas for full execution. This represents a significant 43.02\% reduction in total gas consumption compared to existing pairing-based constructions, saving 67,035 gas per on-chain verification.

We present Frobenius-UOV, a multivariate public-key signature scheme in the Unbalanced Oil and Vinegar (UOV) family. The scheme replaces generic quadratic polynomials with a structured subclass based on Frobenius-type quadratic forms, yielding a compressed public-key representation while retaining the efficient UOV signing procedure. We describe the key-generation, signing, and verification algorithms, and we detail the derivation of the public system from a compact secret description. We discuss security in the standard multivariate setting, including direct algebraic attacks and key-recovery approaches, and we formalize the underlying computational problems induced by the proposed structure. Finally, we report implementation results quantifying the costs of key generation, signing, and verification, as well as the resulting public-key and signature sizes.

Poseidon2 and Neptune use sparse S-box activation in internal partial rounds to reduce arithmetization cost. This structure makes linear subspace trails relevant to algebraic attacks. If the initial state is restricted to a suitable linear subspace, then subsequent internal states may remain in prescribed linear subspaces for a number of rounds. The corresponding partial rounds therefore do not increase the degree of the resulting polynomial system. Existing analyses use this property to estimate the complexity of reduced round preimage attacks. It is therefore important to understand how long such linear subspace trails can persist.

We revisit infinite and finite linear subspace trails in Poseidon-like designs. First, we study the invariant subspace conditions that give rise to infinitely long trails. We relate these conditions to the characteristic polynomials of the Cauchy MDS matrices used in these permutations, and we discuss qualitatively why they are unlikely over fields of large characteristic. Second, we analyze finite linear trails for internal partial rounds in a state of width $t$, where each round activates $s$ S-box coordinates. Under the rank growth condition stated in this paper, when no such invariant subspace exists, a finite trail has length at most $\lceil t/s\rceil-1$. For Poseidon2 and Neptune, $s=1$, this gives at most $t-1$ consecutive linearized internal partial rounds. Considering preimage attacks in sponge mode with rate $r$, capacity $c$, and digest size $d$, the available extra constraint budget is $Ec=r-\min\{c,d\}$. Together, the finite trail bound and this constraint budget determine how many internal partial rounds can be linearized in the corresponding attack model.

Multiscalar multiplication (MSM) is a core operation in modern cryptographic systems, commonly used in various applications such as Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge (ZK-SNARKs) and Homomorphic Encryption. In elliptic curve–based ZK-SNARK constructions, MSM accounts for up to 80–90\% of the total proof generation time, making its optimization critical to improving overall protocol performance. Despite significant progress in accelerating MSM through algorithmic techniques such as Pippenger’s method, existing implementations remain vulnerable to timing attacks due to irregular scalar representations and conditional operations on zero digits.\\

In this paper, we revisit the original Pippenger’s MSM algorithm, proposing novel modifications that achieve resistance to timing attacks while at the same time increasing its performance by almost 25\%. Our main contribution is a new scalar recoding algorithm that transforms conventional $q$-ary representations containing zero digits into equivalent non-zero representations. This ensures that all scalar digits are processed uniformly, eliminating timing-based side-channel leaks. Building on this recoding technique, we introduce a secure variant of Pippenger’s bucket method, that avoids zero digits. Finally, we demonstrate that employing an endomorphism-based splitting yields shorter digit expansions and further efficiency gains. To the best of our knowledge, this is the first MSM algorithm explicitly designed to mitigate timing attacks within the Pippenger bucket method framework.