On Adaptive Bandwidth Selection For Efficient Mia

Recently, a generic DPA attack using the mutual information index as the side channel distinguisher has been introduced. Mutual Information Analysis's (MIA) main interest is its claimed genericity. However, it requires the estimation of various probability density functions (PDF), which is a task that involves the complicated problem of selecting tuning parameters. This problem could be the cause of the lower efficiency of MIA that has been reported. In this paper, we introduce an approach that selects the tuning parameters with the goal of optimizing the performance of MIA. Our approach differs from previous works in that it maximizes the ability of MIA to discriminate one key among all guesses rather than optimizing the accuracy of PDF estimates. Application of this approach to various leakage traces confirms the soundness of our proposal.