Neyman's Smoothness Test: A Trade-Off between Moment-Based and Distribution-Based Leakage Detections

Si Gao; Elisabeth Oswald; Yan Yan

doi:10.1109/TIFS.2021.3108570

Neyman's Smoothness Test: A Trade-Off between Moment-Based and Distribution-Based Leakage Detections

Si Gao^*, Elisabeth Oswald, Yan Yan

^*Corresponding author for this work

Computer Science

Research output: Contribution to journal › Article › peer-review

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 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 2-test). We also find that there is a sweet-spot where Neyman's test outperforms both the t -test and the 2-test. Realistic measurements confirm that such a sweet-spot is relevant in practice for detecting implementation flaws.

Original language	English
Pages (from-to)	4494-4506
Number of pages	13
Journal	IEEE Transactions on Information Forensics and Security
Volume	16
Early online date	30 Aug 2021
DOIs	https://doi.org/10.1109/TIFS.2021.3108570
Publication status	Published - 8 Sept 2021

Bibliographical note

Funding Information:
Manuscript received May 18, 2021; revised July 18, 2021; accepted August 10, 2021. Date of publication August 30, 2021; date of current version September 8, 2021. This work was supported by European Research Council (ERC) under Consolidator Grant 725042 (Sound and Early Assessment of Leakage for Embedded Software, SEAL). The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Georg Sigl. (Corresponding author: Si Gao.) The authors are with the Department of AI and Cybersecurity, University of Klagenfurt, 9020 Klagenfurt, Austria (e-mail: si.gao@aau.at; elisabeth.oswald@aau.at; yan.yan@aau.at). Digital Object Identifier 10.1109/TIFS.2021.3108570

Publisher Copyright:
© 2005-2012 IEEE.

Keywords

Leakage detection
Neyman's smoothness test

ASJC Scopus subject areas

Safety, Risk, Reliability and Quality
Computer Networks and Communications

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10.1109/TIFS.2021.3108570

Cite this

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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 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 2-test). We also find that there is a sweet-spot where Neyman's test outperforms both the t -test and the 2-test. Realistic measurements confirm that such a sweet-spot is relevant in practice for detecting implementation flaws.",

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Neyman's Smoothness Test: A Trade-Off between Moment-Based and Distribution-Based Leakage Detections

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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