What can Information Guess? Guessing Advantage vs. R\'enyi Entropy for Small Leakages

Author:

Julien Béguinot, Olivier Rioul

Keyword:

Computer Science, Information Theory, Information Theory (cs.IT)

journal:

date:

2024-01-30 00:00:00

Abstract

We leverage the Gibbs inequality and its natural generalization to R\'enyi entropies to derive closed-form parametric expressions of the optimal lower bounds of $\rho$th-order guessing entropy (guessing moment) of a secret taking values on a finite set, in terms of the R\'enyi-Arimoto $\alpha$-entropy. This is carried out in an non-asymptotic regime when side information may be available. The resulting bounds yield a theoretical solution to a fundamental problem in side-channel analysis: Ensure that an adversary will not gain much guessing advantage when the leakage information is sufficiently weakened by proper countermeasures in a given cryptographic implementation. Practical evaluation for classical leakage models show that the proposed bounds greatly improve previous ones for analyzing the capability of an adversary to perform side-channel attacks.

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