International Association
for Cryptologic Research

A recent work of Guo, Johansson and Nguyen (Eprint'23) proposes a promising adaptation of Sieving techniques from lattices to codes, in particular claiming concrete cryptanalytic improvements on various schemes. The core of their algorithm reduces to a Near-Neighbor Search (NNS) problem, for which they devise an ad-hoc approach. In this work we aim for a better theoretical understanding of this approach. First by providing an asymptotic analysis which is not present in the original paper. Second, we propose a more systematic use of known NNS machinery, namely Locality Sensitive Hashing and Filtering (LSH/F), an approach that has been applied very successfully in the case of sieving over lattices. We establish the first baseline for the sieving approach with a decoding complexity of $2^{0.117n}$ for the conventional worst parameters (full distance decoding, complexity maximized over all code rates). Our cumulative improvements, eventually enable us to lower the hardest parameter decoding complexity for SievingISD algorithms to $2^{0.101n}$. While this outperforms the BJMM algorithm (Eurocrypt'12) it falls yet behind the most advanced conventional ISD approach by Both and May (PQCrypto'18). As for lattices, we found the Random-Spherical-Code-Product (RPC) to give the best asymptotic complexity. Moreover, we also consider an alternative that seems specific to the Hamming Sphere, which we believe could be of practical interest, as they plausibly hide less sub-exponential overheads than RPC.

Since 2016’s NIST call for standardization of post-quantum cryptographic primitives, developing efficient post-quantum secure digital signature schemes has become a highly active area of research. The difficulty in constructing such schemes is evidenced by NIST reopening the call in 2022 for digital signature schemes, because of missing diversity in existing proposals. In this work, we introduce the new postquantum digital signature scheme MiRitH. As direct successor of a scheme recently developed by Adj, Rivera-Zamarripa and Verbel (Africacrypt ’23), it is based on the hardness of the MinRank problem and follows the MPC-in-the-Head paradigm. We revisit the initial proposal, incorporate design-level improvements and provide more efficient parameter sets. We also provide the missing justification for the quantum security of all parameter sets following NIST metrics. In this context we design a novel Grover-amplified quantum search algorithm for solving the MinRank problem that outperforms a naive quantum brute-force search for the solution.MiRitH obtains signatures of size 5.7 kB for NIST category I security and therefore competes for the smallest signatures among any post-quantum signature following the MPCitH paradigm.At the same time MiRitH offers competitive signing and verification timings compared to the state of the art. To substantiate those claims we provide extensive implementations. This includes a reference implementation as well as optimized constant-time implementations for Intel processors (AVX2), and for the ARM (NEON) architecture. The speedup of our optimized AVX2 implementation relies mostly on a redesign of the finite field arithmetic, improving over existing implementations as well as an improved memory management.

Cryptographic constructions often base security on structured problem variants to enhance efficiency or to enable advanced functionalities. This led to the introduction of the Regular Syndrome Decoding (RSD) problem, which guarantees that a solution to the Syndrome Decoding (SD) problem follows a particular block-wise structure. Despite recent attacks exploiting that structure by Briaud and Øygarden (Eurocrypt ’23) and Carozza, Couteau and Joux (CCJ, Eurocrypt ’23), many questions about the impact of the regular structure on the problem hardness remain open. In this work we initiate a systematic study of the hardness of the RSD problem starting from its asymptotics. We classify different parameter regimes revealing large regimes for which RSD instances are solvable in polynomial time and on the other hand regimes that lead to particularly hard instances. Against previous perceptions, we show that a classification solely based on the uniqueness of the solution is not sufficient for isolating the worst case parameters. Further, we provide an in-depth comparison between SD and RSD in terms of reducibility and computational complexity, identifying regimes in which RSD instances are actually *harder* to solve. We provide the first asymptotic analyses of the algorithms presented by CCJ, establishing their worst case decoding complexities as $2^{0.141n}$ and $2^{0.135n}$, respectively. We then introduce *regular-ISD* algorithms by showing how to tailor the whole machinery of advanced Information Set Decoding (ISD) techniques from attacking SD to the RSD setting. The fastest regular-ISD algorithm improves the worst case decoding complexity significantly to $2^{0.113n}$. Eventually, we show that also with respect to suggested parameters regular-ISD outperforms previous approaches in most cases, reducing security levels by up to 30 bits.

We propose new time-memory trade-offs for the random subset sum problem defined on $(a_1,\ldots,a_n,t)$ over $\Z_{2^n}$. Our trade-offs yield significant running time improvements for every fixed memory limit $M\geq2^{0.091n}$. Furthermore, we interpolate to the running times of the fastest known algorithms when memory is not limited. Technically, our design introduces a pruning strategy to the construction by Becker-Coron-Joux (BCJ) that allows for an exponentially small success probability. We compensate for this reduced probability by multiple randomized executions. Our main improvement stems from the clever reuse of parts of the computation in subsequent executions to reduce the time complexity per iteration. As an application of our construction, we derive the first non-trivial time-memory trade-offs for Information Set Decoding (ISD) algorithms. Our new algorithms improve on previous (implicit) trade-offs asymptotically as well as practically. Moreover, our optimized implementation also improves on \emph{running time}, due to reduced memory access costs. We demonstrate this by obtaining a new record computation in decoding quasi-cyclic codes (QC-3138). Using our newly obtained data points we then extrapolate the hardness of suggested parameter sets for the NIST PQC fourth round candidates McEliece, BIKE and HQC, lowering previous estimates by up to 6 bits and further increasing their reliability.

The LWE problem is one of the prime candidates for building the most efficient post-quantum secure public key cryptosystems. Many of those schemes, like Kyber, Dilithium or those belonging to the NTRU-family, such as NTRU-HPS, -HRSS, BLISS or GLP, make use of small max norm keys to enhance efficiency. The best attack on these schemes is a hybrid attack, which combines combinatorial techniques and lattice reduction. While lattice reduction is not known to be able to exploit the small max norm choices, May recently showed (Crypto 2021) that such choices allow for more efficient combinatorial attacks. However, these combinatorial attacks suffer enormous memory requirements, which render them inefficient in realistic attack scenarios and, hence, make their general consideration when assessing security questionable. Therefore, more memory-efficient substitutes for these algorithms are needed. In this work, we provide new combinatorial algorithms for recovering small max norm LWE secrets using only a polynomial amount of memory. We provide analyses of our algorithms for secret key distributions of current NTRU, Kyber and Dilithium variants, showing that our new approach outperforms previous memory-efficient algorithms. For instance, considering uniformly random ternary secrets of length $n$ we improve the best known time complexity for polynomial memory algorithms from $2^{1.063n}$ down-to $2^{0.926n}$. We obtain even larger gains for LWE secrets in $\{-m,\ldots,m\}^n$ with $m=2,3$ as found in Kyber and Dilithium. For example, for uniformly random keys in $\{-2,\ldots,2\}^n$ as is the case for Dilithium we improve the previously best time from $2^{1.742n}$ down-to $2^{1.282n}$. Our fastest algorithm incorporates various different algorithmic techniques, but at its heart lies a nested collision search procedure inspired by the Nested-Rho technique from Dinur, Dunkelman, Keller and Shamir (Crypto 2016). Additionally, we heavily exploit the representation technique originally introduced in the subset sum context to make our nested approach efficient.

The selection of secure parameter sets requires an estimation of the attack cost to break the respective cryptographic scheme instantiated under these parameters. The current NIST standardization process for post-quantum schemes makes this an urgent task, especially considering the announcement to select final candidates by the end of 2021. For code-based schemes, recent estimates seemed to contradict the claimed security of most proposals, leading to a certain doubt about the correctness of those estimates. Furthermore, none of the available estimates includes most recent algorithmic improvements on decoding linear codes, which are based on information set decoding (ISD) in combination with nearest neighbor search. In this work we observe that \emph{all} major ISD improvements are build on nearest neighbor search, explicitly or implicitly. This allows us to derive a framework from which we obtain \emph{practical} variants of all relevant ISD algorithms including the most recent improvements. We derive formulas for the practical attack costs and make those online available in an easy to use estimator tool written in python and C. Eventually, we provide classical and quantum estimates for the bit security of all parameter sets of current code-based NIST proposals.

With the recent shift to post-quantum algorithms it becomes increasingly important to provide precise bit-security estimates for code-based cryptography such as McEliece and quasi-cyclic schemes like BIKE and HQC. While there has been significant progress on information set decoding (ISD) algorithms within the last decade, it is still unclear to which extent this affects current cryptographic security estimates. We provide the first concrete implementations for representation-based ISD, such as May-Meurer-Thomae (MMT) or Becker-Joux-May-Meurer (BJMM), that are parameter-optimized for the McEliece and quasi-cyclic setting. Although MMT and BJMM consume more memory than naive ISD algorithms like Prange, we demonstrate that these algorithms lead to significant speedups for practical cryptanalysis already for cryptographic instances of medium security level (around 60 bit). More concretely, we provide data for the record computations of McEliece-1223 and McEliece-1284 (old record: 1161), and for the quasi-cyclic setting up to dimension 2918 (before: 1938). Based on our record computations we extrapolate to the bit-security level of the proposed BIKE, HQC and McEliece parameters in NIST's standardization process. For BIKE/HQC, we also show how to transfer the Decoding-One-Out-of-Many (DOOM) technique to MMT/BJMM. Although we achieve significant DOOM speedups, our estimates confirm the bit-security levels of BIKE and HQC. For the proposed McEliece round-3 parameter sets of 192 and 256 bit, however, our extrapolation indicates a security level overestimate by roughly 20 and 10 bits, respectively, i.e., the high-security McEliece instantiations may be a bit less secure than desired.

In a so-called partial key exposure attack one obtains some information about the secret key, e.g. via some side-channel leakage. This information might be a certain fraction of the secret key bits (erasure model) or some erroneous version of the secret key (error model). The goal is to recover the secret key from the leaked information. There is a common belief that, as opposed to e.g. the RSA cryptosystem, most post-quantum cryptosystems are usually resistant against partial key exposure attacks. We strongly question this belief by constructing partial key exposure attacks on code-based, multivariate, and lattice-based schemes (BIKE, Rainbow and NTRU). Our attacks exploit the redundancy that modern PQ cryptosystems inherently use for efficiency reasons. The application and development of techniques from information set decoding plays a crucial role for achieving our results. On the theoretical side, we show non-trivial information leakage bounds that allow for a polynomial time key recovery attack. As an example, for all schemes the knowledge of a constant fraction of the secret key bits suffices to reconstruct the full key in polynomial time. Even if we no longer insist on polynomial time attacks, most of our attacks extend well and remain feasible up to large erasure and error rates. In the case of BIKE for example we obtain attack complexities around 60 bits when half of the secret key bits are erased, or a quarter of the secret key bits are faulty. Our results show that even highly error-prone key leakage of modern PQ cryptosystems may lead to full secret key recoveries.

We propose two heuristic polynomial memory collision finding algorithms for the low Hamming weight discrete logarithm problem in any abelian group $G$. The first one is a direct adaptation of the Becker-Coron-Joux (BCJ) algorithm for subset sum to the discrete logarithm setting. The second one significantly improves on this adaptation for all possible weights using a more involved application of the representation technique together with some new Markov chain analysis. In contrast to other low weight discrete logarithm algorithms, our second algorithm's time complexity interpolates to Pollard's $|G|^{\frac 1 2}$ bound for general discrete logarithm instances. We also introduce a new heuristic subset sum algorithm with polynomial memory that improves on BCJ's $2^{0.72n}$ time bound for random subset sum instances $a_1, \ldots, a_n, t \in \Z_{2^n}$. Technically, we introduce a novel nested collision finding for subset sum -- inspired by the NestedRho algorithm from Crypto '16 -- that recursively produces collisions. We first show how to instantiate our algorithm with run time $2^{0.649n}$. Using further tricks, we are then able to improve its complexity down to $2^{0.645n}$.

The slightly subexponential algorithm of Blum, Kalai and Wasserman (BKW) provides a basis for assessing LPN/LWE security. However, its huge memory consumption strongly limits its practical applicability, thereby preventing precise security estimates for cryptographic LPN/LWE instantiations.We provide the first time-memory trade-offs for the BKW algorithm. For instance, we show how to solve LPN in dimension k in time $$2^{\frac{4}{3} \frac{k}{\log k} }$$ and memory $$2^{\frac{2}{3} \frac{k}{\log k} }$$. Using the Dissection technique due to Dinur et al. (Crypto ’12) and a novel, slight generalization thereof, we obtain fine-grained trade-offs for any available (subexponential) memory while the running time remains subexponential.Reducing the memory consumption of BKW below its running time also allows us to propose a first quantum version QBKW for the BKW algorithm.