Gradient visualization for general characterization in profiling attacks

DOI10.1007/978-3-030-16350-1_9zbMath1522.94024OpenAlexW2922474087MaRDI QIDQ6075009

Cécile Dumas, Loïc Masure, Emmanuel Prouff

Publication date: 20 October 2023

Published in: Constructive Side-Channel Analysis and Secure Design (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-030-16350-1_9

zbMATH Keywords

characterizationdeep learningprofiling attacksside channel analysispoints of interest

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Cryptography (94A60) Channel models (including quantum) in information and communication theory (94A40)

Related Items (5)

On the influence of optimizers in deep learning-based side-channel analysis ⋮ Learning when to stop: a mutual information approach to prevent overfitting in profiled side-channel analysis ⋮ Reinforcement learning-based design of side-channel countermeasures ⋮ Focus is key to success: a focal loss function for deep learning-based side-channel analysis ⋮ Kilroy was here: the first step towards explainability of neural networks in profiled side-channel analysis

This page was built for publication: Gradient visualization for general characterization in profiling attacks