Deep Learning on Side-Channel Analysis

This chapter provides an overview of recent applications of deep learning to profiled side-channel analysis (SCA). The advent of deep neural networks (mainly multiple layer perceptrons and convolutional neural networks) as a learning algorithm for profiled SCA opened several new directions and possibilities to explore the occurrence of side-channel leakages from different categories of systems. This is particularly important for designers to verify to what extent an adversary can extract sensitive information when possessing state-of-the-art attack methods. Deep learning is a fast-evolving technology that provides several advantages in profiled SCA and we summarize what are the main directions and results obtained by the research community.