Automatic Search of Meet-in-the-Middle Differential Fault Analysis on AES-like Ciphers

Qingyuan Yu, Xiaoyang Dong, Lingyue Qin, Yongze Kang, Keting Jia, Xiaoyun Wang, Guoyan Zhang
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引用次数: 1

Abstract

Fault analysis is a powerful technique to retrieve secret keys by exploiting side-channel information. Differential fault analysis (DFA) is one of the most powerful threats utilizing differential information between correct and faulty ciphertexts and can recover keys for symmetric-key cryptosystems efficiently. Since DFA usually targets the first or last few rounds of the block ciphers, some countermeasures against DFA only protect the first and last few rounds for efficiency. Therefore, to explore how many rounds DFA can affect is very important to make sure how many rounds to protect in practice. At CHES 2011, Derbez et al. proposed an improved DFA on AES based on MitM approach, which covers one more round than previous DFAs. To perform good (or optimal) MitM DFA on block ciphers, the good (or optimal) attack configurations should be identified, such as the location where the faults inject, the matching point with differential relationship, and the two independent computation paths where two independent subsets of the key are involved. In this paper, we formulate the essential ideas of the construction of the attack, and translate the problem of searching for the best MitM DFA into optimization problems under constraints in Mixed-Integer-Linear-Programming (MILP) models. With the models, we achieve more powerful and practical DFA attacks on SKINNY, CRAFT, QARMA, PRINCE, PRINCEv2, and MIDORI with faults injected in 1 to 9 earlier rounds than the best previous DFAs.
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类aes密码中相遇差分故障分析的自动搜索
故障分析是利用侧信道信息检索密钥的一种有效技术。差分故障分析(DFA)是利用正确密文和错误密文之间的差分信息的一种最强大的威胁,可以有效地恢复对称密钥密码系统的密钥。由于DFA通常针对分组密码的第一轮或最后几轮,因此为了提高效率,一些针对DFA的对策只保护第一轮和最后几轮。因此,研究DFA能影响多少发子弹,对于实践中确定保护多少发子弹具有十分重要的意义。在2011年的CHES上,Derbez等人提出了一种基于MitM方法的AES改进DFA,该方法比以前的DFA多涵盖一轮。为了对分组密码执行良好(或最优)的MitM DFA,需要识别出良好(或最优)的攻击配置,如故障注入的位置、具有微分关系的匹配点以及涉及两个独立密钥子集的两个独立计算路径。在本文中,我们阐述了攻击构造的基本思想,并将寻找最佳MitM DFA问题转化为混合整数线性规划(MILP)模型约束下的优化问题。通过这些模型,我们实现了对SKINNY, CRAFT, QARMA, PRINCE, PRINCEv2和MIDORI的更强大和实用的DFA攻击,并在1到9轮之前注入错误,而不是之前最好的DFA。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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