Deep learning-driven side-channel analysis (SCA) is a promising approach to side-channel
analytic profiling. Recent studies have shown that neural networks can successfully attack …

Hyperparameter tuning represents one of the main challenges in deep learning-based
profiling side-channel analysis. For each different side-channel dataset, the typical …

The attacks that leverage the side-channels produced by processes running on mobile and
IoT devices are a concrete threat for cyber–physical systems. This special issue is focused …

This paper introduces a deep learning modular network for side-channel analysis. Our
approach features a deep learning architecture with the capability to exchange parts …

With the rapid advancement of deep learning, the neural network has become the primary
approach for non-profiled side-channel attacks. Nevertheless, challenges arise in practical …

Side-channel analysis is one of the vulnerabilities in IoT's cryptographic systems. To present
reliable side-channel analysis results, it is crucial to collect considerable amounts of power …

Side-channel attack (SCA) based on machine learning has proved to be a valid technique in
cybersecurity, especially subjecting to the symmetric-key crypto implementations in serial …

Cryptographic algorithms on devices are vulnerable to the so-called side-channel attacks
(SCAs). The security evaluation of the cryptographic circuits is necessary to provide earlier …

Abstract Machine learning techniques are commonly employed in the context of Side
Channel Analysis attacks. The clustering algorithms can be successfully used as classifiers …

Evaluating side-channel analysis (SCA) security is a complex process, involving applying
several techniques whose success depends on human engineering. Therefore, it is crucial …