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Template Attacks vs. Machine Learning Revisited (and the Curse of Dimensionality in Side-Channel Analysis)
[chapter]
2015
Lecture Notes in Computer Science
Template attacks and machine learning are two popular approaches to profiled side-channel analysis. In this paper, we aim to contribute to the understanding of their respective strengths and weaknesses, with a particular focus on their curse of dimensionality. For this purpose, we take advantage of a well-controlled simulated experimental setting in order to put forward two important intuitions. First and from a theoretical point of view, the data complexity of template attacks is not sensitive
doi:10.1007/978-3-319-21476-4_2
fatcat:6ktccfp53rcw7krwcks5xj44ze