Welcome to the resource topic for 2021/1039
Title:
Neyman’s Smoothness Test: a Trade-off between Moment-based and Distribution-based Leakage Detections
Authors: Si Gao, Elisabeth Oswald, Yan Yan
Abstract:Leakage detection tests have become an indispensable tool for testing implementations featuring side channel countermeasures such as masking. Whilst moment-based techniques such as the Welch’s t-test are universally powerful if there is leakage in a central moment, they naturally fail if this is not the case. Distribution-based techniques such as the χ2-test then come to the rescue, but they have shown not to be robust with regards to noise. In this paper, we propose a novel leakage detection technique based on Neyman’s smoothness test. We find that our new test is robust with respect to noise (similar to the merit of Welch’s t-test), and can pick up on leakage that is not located in central moments (similar to the merit of the χ2-test). We also find that there is a sweet-spot where Neyman’s test outperforms both the t-test and the χ2-test. Realistic measurements confirm that such a sweet-spot is relevant in practice for detecting implementation flaws.
ePrint: https://eprint.iacr.org/2021/1039
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