Score-Based vs. Probability-Based Enumeration - A Cautionary Note

The fair evaluation of leaking devices generally requires to come with the best possible distinguishers to extract and exploit side-channel information. While the need of a sound model for the leakages is a well known issue, the risks of additional errors in the post-processing of the attack results (with key enumeration/key rank estimation) are less investigated. Namely, optimal post-processing is known to be possible with distinguishers outputting probabilities (e.g. template attacks), but the impact of a deviation from this context has not been quantified so far. We therefore provide a consolidating experimental analysis in this direction, based on simulated and actual measurements. Our main conclusions are twofold. We first show that the concrete impact of heuristic scores such as produced with a correlation power analysis can lead to non-negligible post-processing errors. We then show that such errors can be mitigated in practice, with Bayesian extensions or specialized distinguishers (e.g. on-the-fly linear regression).