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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


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.

Available format(s)
Publication info
Published elsewhere. Minor revision. IEEE TIFS
Leakage detectionNeyman's smoothness test
Contact author(s)
si-gao @ outlook com
elisabeth oswald @ aau at
yanyansmajesty @ outlook com
2021-08-16: received
Short URL
Creative Commons Attribution


      author = {Si Gao and Elisabeth Oswald and Yan Yan},
      title = {Neyman’s Smoothness Test: a Trade-off between Moment-based and Distribution-based Leakage Detections},
      howpublished = {Cryptology ePrint Archive, Paper 2021/1039},
      year = {2021},
      note = {\url{https://eprint.iacr.org/2021/1039}},
      url = {https://eprint.iacr.org/2021/1039}
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