Side-channel attacks pose a serious threat to implementations of cryptographic algorithms. Template attacks are probabilistic side channel attacks, which assume a Gaussian noise model. Selecting automatically the meaningful time samples in side-channel leakage traces is an important problem in the application of template attacks and it usually relies on heuristics. In this work, we propose a new dimension reduction method which is different from classical statistical tools to solve this problem.
Template Attack, PCA, SCEC
Cross entropy,Algorithm design,Subspace topology,Computer science,Cryptography,Theoretical computer science,Heuristics,Side channel attack,Artificial intelligence,Probabilistic logic,Gaussian noise,Machine learning