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引用次数: 2
摘要
智能IC卡可能遭受密码分析之外的攻击。侧香奈儿攻击(SCA)是通过收集智能IC卡实现过程中泄露的信息来寻找密钥。最近的出版物表明,将机器学习算法应用于SCA分析是可能的。本文介绍了如何将最先进的集成方法应用于SM4算法。集成方法采用了多种算法,得到了较好的效果。与传统的模板攻击(TA)方法相比,我们采用支持向量机(SVM)和k- nn (k近邻)算法。我们研究了改变距离函数对k-NN分类器精度的影响。我们还简要分析了为什么集成方法可以解决这个问题。
Side Channel Attack on SM4 Algorithm with Ensemble Method
Smart IC card may undergo attacks that beyond cryptanalysis. Side Chanel Attack(SCA) gathers information leaked from implementations of smart IC card to find the secret key. Recent Publications had shown that it is possible to apply machine learning algorithms on SCA analysis. This article shows how to apply the ensemble method, one of the state of art methods, on SM4 algorithm. Ensemble method uses multiple algorithms to get better result. We apply SVM (support vector machine) and k-NN (k nearest neighbors) algorithms, compared with traditional template attack (TA) method. We investigated the impact of changing the distance function on the accuracy of the k-NN classifier. We also make a brief analysis on why does the ensemble method work on this problem.