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 side-channel analysis is
the possibility of skip** the feature engineering process. Despite that, most recent …

With increasing expansion of the Internet of Things, embedded devices equipped with
cryptographic modules become an important factor to protect sensitive data. Even though …

Using information-theoretic tools, this paper establishes a mathematical link between the
probability of success of a side-channel attack and the minimum number of queries to reach …

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

Profiled side-channel attacks represent a practical threat to digital devices, thereby having
the potential to disrupt the foundation of e-commerce, the Internet of Things (IoT), and smart …

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

Profiling attacks, especially those based on machine learning proved as very successful
techniques in recent years when considering side-channel analysis of block ciphers …

Deep learning-based side-channel analysis performance heavily depends on the dataset
size and the number of instances in each target class. Both small and imbalanced datasets …