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

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 …

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 field of image recognition, machine learning technologies, especially deep learning,
have been rapidly advancing alongside the advances of hardware such as GPUs. In image …

In recent years, deep learning has become an attractive ingredient to side-channel analysis
(SCA) due to its potential to improve the success probability or enhance the performance of …

Deep learning (DL) has proven to be very effective for image recognition tasks, with a large
body of research on various model architectures for object classification. Straight-forward …

Abstract Deep Learning based Side-Channel Attacks (DL-SCA) are an emerging security
assessment method increasingly being adopted by the majority of certification schemes and …

While several works have explored the application of deep learning for efficient profiled side-
channel analysis, explainability, or, in other words, what neural networks learn remains a …

In recent years, the convolutional neural networks (CNNs) have received a lot of interest in
the side-channel community. The previous work has shown that CNNs have the potential of …

Profiling attacks, especially those based on machine learning, proved to be very successful
techniques in recent years when considering the side-channel analysis of symmetric-key …