Side-channel attacks represent a realistic and serious threat to the security of embedded
devices for already almost three decades. A variety of attacks and targets they can be …

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

One of the main promoted advantages of deep learning in profiling sidechannel analysis is
the possibility of skip** the feature engineering process. Despite that, most recent …

Profiled side-channel analysis (SCA) leverages leakage from cryptographic
implementations to extract the secret key. When combined with advanced methods in neural …

The appearance of deep neural networks for Side-Channel leads to strong power analysis
techniques for detecting secret information of physical cryptography implementations …

The efficiency of the profiling side-channel analysis can be significantly improved with
machine learning techniques. Although powerful, a fundamental machine learning limitation …

Despite considerable achievements of deep learning-based side-channel analysis,
overfitting represents a significant obstacle in finding optimized neural network models. This …

Guessing entropy is a common metric in side-channel analysis, and it represents the
average key rank position of the correct key among all possible key guesses. By evaluating …

This work investigates using Homomorphic Encryption (HE) to assist the security evaluation
of cryptographic devices without revealing side-channel information. For the first time, we …

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