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Evaluating and Improving Linear Regression Based Profiling: On the Selection of Its Regularization
Journal of Computer Science and Technology ( IF 1.2 ) Pub Date : 2020-09-30 , DOI: 10.1007/s11390-020-9669-0
Xiang-Jun Lu , Chi Zhang , Da-Wu Gu , Jun-Rong Liu , Qian Peng , Hai-Feng Zhang

Side-channel attacks (SCAs) play an important role in the security evaluation of cryptographic devices. As a form of SCAs, profiled differential power analysis (DPA) is among the most powerful and efficient by taking advantage of a profiling phase that learns features from a controlled device. Linear regression (LR) based profiling, a special profiling method proposed by Schindler et al., could be extended to generic-emulating DPA (differential power analysis) by on-the-fly profiling. The formal extension was proposed by Whitnall et al. named SLR-based method. Later, to improve SLR-based method, Wang et al. introduced a method based on ridge regression. However, the constant format of L-2 penalty still limits the performance of profiling. In this paper, we generalize the ridge-based method and propose a new strategy of using variable regularization. We then analyze from a theoretical point of view why we should not use constant penalty format for all cases. Roughly speaking, our work reveals the underlying mechanism of how different formats affect the profiling process in the context of side channel. Therefore, by selecting a proper regularization, we could push the limits of LR-based profiling. Finally, we conduct simulation-based and practical experiments to confirm our analysis. Specifically, the results of our practical experiments show that the proper formats of regularization are different among real devices.

中文翻译:

评估和改进基于线性回归的分析:关于其正则化的选择

旁道攻击 (SCA) 在密码设备的安全评估中发挥着重要作用。作为 SCA 的一种形式,分析差分功率分析 (DPA) 是最强大和最有效的方法之一,它利用分析阶段从受控设备中学习特征。基于线性回归 (LR) 的分析是 Schindler 等人提出的一种特殊分析方法,可以通过动态分析扩展到通用模拟 DPA(差分功率分析)。Whitnall 等人提出了正式的扩展。命名为基于 SLR 的方法。后来,为了改进基于 SLR 的方法,Wang 等人。介绍了一种基于岭回归的方法。然而,L-2惩罚的恒定格式仍然限制了分析的性能。在本文中,我们推广了基于岭的方法,并提出了一种使用变量正则化的新策略。然后我们从理论的角度分析为什么我们不应该对所有情况都使用恒定惩罚格式。粗略地说,我们的工作揭示了不同格式如何影响侧信道上下文中的分析过程的潜在机制。因此,通过选择适当的正则化,我们可以突破基于 LR 的分析的极限。最后,我们进行了基于模拟的实际实验来证实我们的分析。具体来说,我们的实际实验结果表明,真实设备之间的正确正则化格式是不同的。我们的工作揭示了不同格式如何影响侧信道环境中的分析过程的潜在机制。因此,通过选择适当的正则化,我们可以突破基于 LR 的分析的极限。最后,我们进行了基于模拟的实际实验来证实我们的分析。具体来说,我们的实际实验结果表明,真实设备之间的正确正则化格式是不同的。我们的工作揭示了不同格式如何影响侧信道环境中的分析过程的潜在机制。因此,通过选择适当的正则化,我们可以突破基于 LR 的分析的极限。最后,我们进行了基于模拟的实际实验来证实我们的分析。具体来说,我们的实际实验结果表明,真实设备之间的正确正则化格式是不同的。
更新日期:2020-09-30
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