Efficient Regression-Based Linear Discriminant Analysis for Side-Channel Security Evaluations Towards Analytical Attacks against 32-bit Implementations

Cassiers, Gaëtan;Devillez, Henri;Standaert, François-Xavier;Udvarhelyi, Balazs
(2023) IACR Transactions on Cryptographic Hardware and Embedded SystemsISSN 2569-2925, Vol. 2023, No. 3, pp. 270–293.DOI:10.46586 — Vol. 2023, n° 3, p. 270-293 (2023)

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Abstract
32-bit software implementations become increasingly popular for embeddedsecurity applications. As a result, profiling 32-bit target intermediate values becomesincreasingly needed to evaluate their side-channel security. This implies the need ofstatistical tools that can deal with long traces and large number of classes. Whilethere are good options to solve these issues separately (e.g., linear regression andlinear discriminant analysis), the current state of the art lacks efficient tools to solvethem jointly. To the best of our knowledge, the best-known option is to fragmentthe profiling in smaller parts, which is suboptimal from the information theoreticviewpoint. In this paper, we therefore revisit regression-based linear discriminantanalysis, which combines linear regression and linear discriminant analysis, andimprove its efficiency so that it can be used for profiling long traces correspondingto 32-bit implementations. Besides introducing the optimizations needed for thispurpose, we show how to use regression-based linear discriminant analysis in order toobtain efficient bounds for the perceived information, an information theoretic metriccharacterizing the security of an implementation against profiled attacks. We alsocombine this tool with optimizations of soft analytical side-channel attack that applyto bitslice implementations. We use these results to attack a 32-bit implementation ofISAP instantiated with Ascon’s permutation, and show that breaking the initializationof its re-keying in one trace is feasible for determined adversaries
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Cassiers, G., Devillez, H., Standaert, F.-X., & Udvarhelyi, B. (2023). Efficient Regression-Based Linear Discriminant Analysis for Side-Channel Security Evaluations Towards Analytical Attacks against 32-bit Implementations. IACR Transactions on Cryptographic Hardware and Embedded SystemsISSN 2569-2925, Vol. 2023, No. 3, pp. 270–293.DOI:10.46586, 2023(3), 270-293. https://doi.org/10.46586/tches.v2023.i3.270-293 (Original work published 2023)