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 …

The deep learning-based side-channel analysis represents a powerful and easy to deploy
option for profiling side-channel attacks. A detailed tuning phase is often required to reach a …

Today, deep neural networks are a common choice for conducting the profiled side-channel
analysis. Such techniques commonly do not require pre-processing, and yet, they can break …

Today, deep neural networks are a common choice for conducting the profiled side-channel
analysis. Unfortunately, it is not trivial to find neural network hyperparameters that would …

The absence of an algorithm that effectively monitors the deep learning models used in side-
channel attacks increases the difficulty of a security evaluation. If an attack is unsuccessful …

Recently deep-learning (DL) techniques have been widely adopted in side-channel power
analysis. A DL-assisted SCA generally consists of two phases: a deep neural network (DNN) …

The use of deep learning techniques to perform side-channel analysis attracted the attention
of many researchers as they obtained good performances with them. Unfortunately, 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 …

Recently deep-learning (DL) techniques have been widely adopted in side-channel analysis
and generally considered the state-of-art method. Specifically, when appropriately trained …

The recent improvements in deep learning (DL) have reshaped the state of the art of side-
channel attacks (SCA) in the field of embedded security. Yet, their``black-box''aspect …