Recent works have demonstrated that deep learning algorithms were very efficient to conduct security evaluations of embedded systems and had many advantages compared to the other methods. A comprehensive study of deep learning algorithms when applied in the context of side-channel analysis and we discuss the links with the classical template attacks. We address the question of the choice of the hyper-parameters for the class of multi-layer perceptron networks and convolutional neural networks. Several benchmarks and rationales are given in the context of the analysis of a masked implementation of the AES algorithm.
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