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Title:
One for All, All for One: A Unified Evaluation Framework for Univariate DPA Attacks
Authors: Jiangshan Long, Chenxu Wang, Changhai Ou, Zhu Wang, Yongbin Zhou, Ming Tang
Abstract:Success Rate (SR) is empirically and theoretically a common metric for evaluating the performance of side-channel attacks. Intuitive expressions of success rate are desirable since they reveal and explain the functional dependence on relevant parameters, such as number of measurements and Signal-to-Noise Ratio (SNR), in a straightforward manner. Meanwhile, existing works more or less expose unsolved fundamental problems, such as strong leakage assumption, difficulty in interpretation of principle, inaccurate evaluation, and inconsideration of high-order SR. In this paper, we first provide an intuitive framework that statistical tests embedded in different univariate DPA attacks are unified as analyzing and comparing visualized vectors in a Euclidean space by using different easy-to-understand metrics. Then, we establish a unified framework to abstract and convert the security evaluations to the problem of finding a boundary in the Euclidean space. With expressions of the boundary, judging whether a DPA attack succeeds in sense of o^{th}-order becomes fairly efficient and intuitive, and the corresponding SR can be calculated theoretically by integral. Finally, we propose an algorithm that is capable of estimating arbitrary order of SR effectively. Our experimental results verify the theory and highlight the superiority. We believe our research raises many new perspectives for comparing and evaluating side-channel attacks, countermeasures and implementations.
ePrint: https://eprint.iacr.org/2022/1360
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