Paper 2022/1780

More Efficient Key Ranking for Optimal Collision Side-Channel Attacks

Abstract

In [Optimal Collision Side-Channel Attacks] we studied collision side-channel attacks, and derived an optimal distinguisher for key ranking. In this note we propose a heuristic estimation procedure for key ranking based on this distinguisher, and provide estimates of lower bounds for secret key ranks in collision side-channel attacks. The procedure employs nonuniform sampling introduced in [MCRank: Monte Carlo Key Rank Estimation for Side-Channel Security Evaluations], and it is more efficient than the subset uniform sampling procedure [A Note on Key Ranking for Optimal Collision Side-Channel Attacks].