International Association for Cryptologic Research

International Association
for Cryptologic Research


Andre Esser


Syndrome Decoding Estimator 📺
Andre Esser Emanuele Bellini
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.
McEliece needs a Break -- Solving McEliece-1284 and Quasi-Cyclic-2918 with Modern ISD
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.
Low Weight Discrete Logarithms and Subset Sum in $2^{0.65n}$ with Polynomial Memory 📺
Andre Esser Alexander May
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 $2^{0.645n}$.
Dissection-BKW 📺
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.