During the years 2018-2024, considerable advancements have been achieved in the use of
deep learning for side channel attacks. The security of cryptographic algorithm …

Given the need for efficient high-performance computing, computer architectures combining
central processing units (CPUs), graphics processing units (GPUs), and field-programmable …

Federated learning (FL) has recently emerged as a striking framework for allowing machine
and deep learning models with thousands of participants to have distributed training to …

We present the first deep learning-based side-channel attack on AES-128 using far field
electromagnetic emissions as a side channel. Our neural networks are trained on traces …

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 this paper, we show that a software implementation of CCA secure Saber KEM protected
by first-order masking and shuffling can be broken by deep learning-based power analysis …

This article presents a critical literature review on the security aspects of field-programmable
gate array (FPGA) devices. FPGA devices present unique challenges to cybersecurity …

Depending on a device's encryption mechanism, a wide variety of tangible details could be
exposed. These leaks are used in side-channel analysis, which is used to get keys. Due to …

Deep Learning Side-Channel Attacks (DLSCAs) have become a realistic threat to
implementations of cryptographic algorithms, such as Advanced Encryption Standard (AES) …

We present a side-channel attack on CRYSTALS-Dilithium, a post-quantum secure digital
signature scheme, with two variants of post-processing. The side-channel attack exploits …