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基于S盒分解的SKINNY_64代数持续故障分析

Algebraic Persistent Fault Analysis of SKINNY_64 Based on S_Box Decomposition.

作者信息

Fang Xing, Zhang Hongxin, Wang Danzhi, Yan Hao, Fan Fan, Shu Lei

机构信息

School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.

Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing 100876, China.

出版信息

Entropy (Basel). 2022 Oct 22;24(11):1508. doi: 10.3390/e24111508.

Abstract

Algebraic persistent fault analysis (APFA), which combines algebraic analysis with persistent fault attacks, brings new challenges to the security of lightweight block ciphers and has received widespread attention since its introduction. Threshold Implementation (TI) is one of the most widely used countermeasures for side channel attacks. Inspired by this method, the SKINNY block cipher adopts the S_box decomposition to reduce the number of variables in the set of algebraic equations and the number of Conjunctive Normal Form (CNF) equations in this paper, thus speeding up the algebraic persistent fault analysis and reducing the number of fault ciphertexts. In our study, we firstly establish algebraic equations for full-round faulty encryption, and then analyze the relationship between the number of fault ciphertexts required and the solving time in different scenarios (decomposed S_boxes and original S_box). By comparing the two sets of experimental results, the success rate and the efficiency of the attack are greatly improved by using S_box decomposition. In this paper, We can recover the master key in a minimum of 2000s using 11 pairs of plaintext and fault ciphertext, while the key recovery cannot be done in effective time using the original S_box expression equations. At the same time, we apply S_box decomposition to another kind of algebraic persistent fault analysis, and the experimental results show that using S_box decomposition can effectively reduce the solving time and solving success rate under the same conditions.

摘要

代数持续故障分析(APFA)将代数分析与持续故障攻击相结合,给轻量级分组密码的安全性带来了新挑战,自提出以来受到了广泛关注。阈值实现(TI)是针对侧信道攻击应用最广泛的对策之一。受此方法启发,本文中SKINNY分组密码采用S盒分解来减少代数方程组中变量的数量以及合取范式(CNF)方程的数量,从而加快代数持续故障分析并减少故障密文的数量。在我们的研究中,我们首先为全轮错误加密建立代数方程,然后分析不同场景(分解后的S盒和原始S盒)下所需故障密文数量与求解时间之间的关系。通过比较两组实验结果,使用S盒分解极大地提高了攻击的成功率和效率。在本文中,使用11对明文和故障密文,我们最少可在2000秒内恢复主密钥,而使用原始S盒表达式方程则无法在有效时间内完成密钥恢复。同时,我们将S盒分解应用于另一种代数持续故障分析,实验结果表明,在相同条件下使用S盒分解可有效减少求解时间并提高求解成功率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b19/9689041/09fa5dcbb18c/entropy-24-01508-g001.jpg

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