Finally, we experimentally show that we can improve the performance of higher-order side-channel attacks by using the proposed technique with domain knowledge ...

A novel approach with deep learning for improving side-channel attacks, especially in a non-profiling scenario, and a new principle of training that trains ...

In this paper, we introduce a novel approach with deep learning for improving side-channel attacks, especially in a non-profiling scenario. We also propose a ...

Apr 20, 2021 · Our techniques described above improved the performance of non-profiled attacks by preprocessing the label data of the autoencoder using.

Sep 4, 2021 · We propose a practical procedure to conduct feature reduction using autoencoders for profiled side-channel leakage evaluations.

Aug 1, 2023 · In this paper, we introduce wavelet scatter transform (WST) and short-time fourier transform (STFT) to non-profiled side-channel analysis domains.

This paper introduces a new method to apply Deep Learning techniques in a Non-Profiled context, where an attacker can only collect a limited number of ...

In this paper, a novel non-profiled side-channel attack architecture is proposed, which incorporates the attention mechanism and derives a corresponding ...

Jul 21, 2023 · Thus, autoencoders have mainly been used to improve attack performance on the same dataset (target) by removing countermeasures and reducing the ...

In this paper, we introduce wavelet scatter transform (WST) and short-time fourier transform (STFT) to non-profiled side-channel analysis domains, to improve ...