Name
Title | ||
|---|---|---|
Neyman'S Smoothness Test: A Trade-Off Between Moment-Based And Distribution-Based Leakage Detections |
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 chi(2)-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 chi(2)-test). We also find that there is a sweet-spot where Neyman's test outperforms both the t -test and the chi(2)-test. Realistic measurements confirm that such a sweet-spot is relevant in practice for detecting implementation flaws. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TIFS.2021.3108570 | IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY |
Keywords | DocType | Volume |
Leakage detection, Neyman's smoothness test | Journal | 16 |
ISSN | Citations | PageRank |
1556-6013 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Si Gao | 1 | 7 | 4.01 |
| Elisabeth Oswald | 2 | 0 | 0.34 |
| Yan Yan | 3 | 0 | 0.34 |