high performance computing on graphics processing units: hgpu.org

In the domain of the Side Channel Attacks, various statistical tools have succeeded to retrieve a secret key, as the Pearson coefficient or the Mutual Information. In this paper we propose to study the Maximal Information Coefficient (MIC) which is a non-parametric method introduced by Reshef et al. [13] to compare two random variables. The MIC is based on the mutual information but it is easier to implement and is robust to the noise. We show how apply this tool in the particular case of the side channel attacks. As in statistics, benefits only appears with drawbacks, the computing complexity of the MIC is high. Therefore, we propose a way to efficiently compute the MIC. The obtained attack called the Maximal Information Coefficient Analysis is compared to the CPA [3] and the MIA [8]. The results show the interest of this approach when the leakage is noisy and bad modeleled.