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 …

AI has provided us with the ability to automate tasks, extract information from vast amounts of
data, and synthesize media that is nearly indistinguishable from the real thing. However …

Machine learning has become mainstream across industries. Numerous examples prove the
validity of it for security applications. In this work, we investigate how to reverse engineer a …

Profiled side-channel analysis based on deep learning, and more precisely Convolutional
Neural Networks, is a paradigm showing significant potential. The results, although scarce …

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. Previous …

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

Recently, several studies have been published on the application of deep learning to
enhance Side-Channel Attacks (SCA). These seminal works have practically validated the …

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 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 …