On the Exact Success Rate of Side Channel Analysis in the Gaussian Model
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Side-channel attacks usually apply a divide-and-conquer strategy, separately recovering different parts of the secret. Their efficiency in practice relies on the adversary ability to precisely assess the success or unsuccess of each of these recoveries. This makes the study of the attack success rate a central problem in side channel analysis. In this paper we tackle this issue in two different settings for the most popular attack, namely the Correlation Power Analysis (CPA). In the first setting, we assume that the targeted subkey is known and we compare the state of the art formulae expressing the success rate as a function of the leakage noise and the algebraic properties of the cryptographic primitive. We also make the link between these formulae and the recent work of Fei et al. at CHES 2012. In the second setting, the subkey is no longer assumed to be known and we introduce the notion of confidence level in an attack result, allowing for the study of different heuristics. Through experiments, we show that the rank evolution of a subkey hypothesis can be exploited to compute a better confidence than considering only the final result.