Paper 2021/1039

Neyman’s Smoothness Test: a Trade-off between Moment-based and Distribution-based Leakage Detections

Si Gao, Elisabeth Oswald, and 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.