Good is not good enough: Deriving optimal distinguishers from communication theory

Annelie Heuser 1, 2, 3 Olivier Rioul 1, 2 Sylvain Guilley 3, 2
1 COMNUM - Communications Numériques
LTCI - Laboratoire Traitement et Communication de l'Information
3 SSH - Secure and Safe Hardware
LTCI - Laboratoire Traitement et Communication de l'Information
Abstract :

We find mathematically optimal side-channel distinguishers by looking at the side-channel as a communication channel. Our methodology can be adapted to any given scenario (device, signal-to-noise ratio, noise distribution, leakage model, etc.). When the model is known and the noise is Gaussian, the optimal distinguisher outperforms CPA and covariance. However, we show that CPA is optimal when the model is only known on a proportional scale. For non-Gaussian noise, we obtain different optimal distinguishers, one for each noise distribution. When the model is imperfectly known, we consider the scenario of a weighted sum of the sensitive variable bits where the weights are unknown and drawn from a normal law. In this case, our optimal distinguisher performs better than the classical linear regression analysis.

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https://hal.telecom-paristech.fr/hal-02286943
Contributor : Telecomparis Hal <>
Submitted on : Friday, September 13, 2019 - 4:23:10 PM
Last modification on : Monday, September 16, 2019 - 9:20:40 AM

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  • HAL Id : hal-02286943, version 1

Citation

Annelie Heuser, Olivier Rioul, Sylvain Guilley. Good is not good enough: Deriving optimal distinguishers from communication theory. 16th Workshop on Cryptographic Hardware and Embedded Systems (CHES 2014), Sep 2014, Busan, South Korea. pp.55-74. ⟨hal-02286943⟩

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