Recent works have demonstrated that deep learning algorithms were efficient to conduct
security evaluations of embedded systems and had many advantages compared to the other …

In the context of the security evaluation of cryptographic implementations, profiling attacks
(aka Template Attacks) play a fundamental role. Nowadays the most popular Template …

Side-channel attacks exploit a physical observable originating from a cryptographic device
in order to extract its secrets. Many practically relevant advances in the field of side-channel …

Today, the deep learning-based side-channel analysis represents a widely researched
topic, with numerous results indicating the advantages of such an approach. Indeed …

As side‐channel analysis and machine learning algorithms share the same objective of
classifying data, numerous studies have been proposed for adapting machine learning to …

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 …

The adoption of deep neural networks for profiled side-channel attacks provides powerful
options for leakage detection and key retrieval of secure products. When training a neural …

With increasing expansion of the Internet of Things, embedded devices equipped with
cryptographic modules become an important factor to protect sensitive data. Even though …

Recently, machine learning algorithms have been utilized by system defenders and
attackers to secure and attack hardware, respectively. In this work, we investigate the impact …

Power side-channel analysis (SCA) has been of immense interest to most embedded
designers to evaluate the physical security of the system. This work presents profiling-based …