用MILP增强ChaCha7的微分线性密码分析

IF 1.7 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
E. Bellini, David Gérault, J. Grados, R. Makarim, Thomas Peyrin
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引用次数: 0

摘要

本文提出了一种改进的差分-线性查码流密码分析方法。我们的主要贡献是新的微分-线性区分器,我们能够建立得益于以下改进:a)我们考虑了更大的搜索空间,包括2位差异(除了1位差异),用于微分-线性轨迹的微分部分开始的差异;B)在差动部分和线性部分之间更好地选择掩模;c)精心制作的MILP工具,可以找到线性部分具有较高相关性的线性轨迹。我们最终获得了一个新的ChaCha区分器,减少到7轮,需要2166.89次计算,将之前的记录(ASIACRYPT 2022)提高了247倍。此外,我们获得了一个ChaCha区分器,减少到7.5轮,需要2251.4次计算,这是ChaCha区分器的第一次减少到7.5轮。使用我们的MILP工具,我们还发现了一个5轮微分-线性区分器。当与概率中性比特(PNB)框架相结合时,我们获得了对ChaCha的密钥恢复攻击减少到7轮,计算复杂度为2206.8,比最近在EUROCRYPT 2022上发表的结果提高了214.2倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Boosting Differential-Linear Cryptanalysis of ChaCha7 with MILP
In this paper, we present an improved differential-linear cryptanalysis of the ChaCha stream cipher. Our main contributions are new differential-linear distinguishers that we were able to build thanks to the following improvements: a) we considered a larger search space, including 2-bit differences (besides 1-bit differences) for the difference at the beginning of the differential part of the differential-linear trail; b) a better choice of mask between the differential and linear parts; c) a carefully crafted MILP tool that finds linear trails with higher correlation for the linear part. We eventually obtain a new distinguisher for ChaCha reduced to 7 rounds that requires 2166.89 computations, improving the previous record (ASIACRYPT 2022) by a factor of 247. Also, we obtain a distinguisher for ChaCha reduced to 7.5 rounds that requires 2251.4 computations, being the first time of a distinguisher against ChaCha reduced to 7.5 rounds. Using our MILP tool, we also found a 5-round differential-linear distinguisher. When combined with the probabilistic neutral bits (PNB) framework, we obtain a key-recovery attack on ChaCha reduced to 7 rounds with a computational complexity of 2206.8, improving by a factor 214.2 upon the recent result published at EUROCRYPT 2022.
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来源期刊
IACR Transactions on Symmetric Cryptology
IACR Transactions on Symmetric Cryptology Mathematics-Applied Mathematics
CiteScore
5.50
自引率
22.90%
发文量
37
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