Deep learning represents a powerful set of techniques for profiling side-channel analysis.
The results in the last few years show that neural network architectures like multilayer …

The side-channel community recently investigated a new approach, based on deep
learning, to significantly improve profiled attacks against embedded systems. Compared to …

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

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 …

In this work, we ask a question whether Convolutional Neural Networks are more suitable for
side-channel attacks than some other machine learning techniques and if yes, in what …

Deep Learning has recently been introduced as a new alternative to perform Side-Channel
analysis [MPP16]. Until now, studies have been focused on applying Deep Learning …

One of the main promoted advantages of deep learning in profiling side-channel analysis is
the possibility of skipping the feature engineering process. Despite that, most recent …

The usage of deep learning in profiled side-channel analysis requires a careful selection of
neural network hyperparameters. In recent publications, different network architectures have …

In the last decade, machine learning-based side-channel attacks have become a standard
option when investigating profiling side-channel attacks. At the same time, the previous state …

In the profiled side-channel analysis, deep learning-based techniques proved to be very
successful even when attacking targets protected with countermeasures. Still, there is no …