双重掩码的模幂算法聚类相关功耗分析攻击

A Cluster Correlation Power Analysis Attack against Modular Exponentiation Algorithm Based on Double Masking Scheme

相关功耗分析方法是模幂算法最常用的攻击方法之一,当设计中使用底数和指数双重掩码防护措施时,现有的相关功耗分析无法使用。采用高阶相关功耗分析可以对这类防护措施实施有效攻击,但会带来噪声、降低攻击准确率,并且攻击过程中分类方法采用人工观察设定阈值方式,攻击效果严重依赖于攻击者的经验。针对以上问题,提出了一种基于聚类相关功耗分析攻击方法,利用模乘之间功耗的相关性特征差异,评估功耗点有效度,提高有效信息利用率,降低噪声和人工参与过程。实验结果表明,针对双层掩码的模幂防范算法,聚类相关功耗分析与现有策略相比,攻击效率和算法通用性得到提升,400条功耗曲线攻击准确率收敛于1。

Correlation power analysis（CPA） which is one of the most useful techniques for side channel attack can not implement a successful attack against the exponent and the message blinding countermeasures on modular exponentiation algorithm. And a successful attack against these protected implementations is performed by the high order CPA. But a lot of noise caused by the high order CPA lead to the less attack accuracy of side channel attack. Moreover, the methods of artificial observation are currently used by setting the threshold in attack process, so the attack effect is heavily dependent on the attacker＇s experience. In order to solve these problems, a cluster CPA is proposed by utilizing correlation characteristics difference between power consumption of modular multiplication to evaluate the effectiveness of power points. The utilization of valid information is improved and the noise and artificial participation are reduced by using the new proposed method. Experiment results demonstrate that the proposed cluster CPA can enhance attack efficiency and attack algorithm generality by comparing with other CPA methods, and only 400 power traces are required to launch the attack with the attack accuracy of 100%.