Hybrid genetic algorithm and deep learning techniques for advanced side-channel attacks
Abstract In recent years, deep learning-based profiling methods have significantly advanced side-channel analysis, yielding promising results. A critical challenge in training effective neural network models lies in hyperparameter optimization. This research introduces a genetic algorithm (GA) frame...
Saved in:
| Main Authors: | Faisal Hameed, Hoda Alkhzaimi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-06375-1 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Deep learning-based profiling side-channel attacks in SPECK cipher
by: Faisal Hameed, et al.
Published: (2025-07-01) -
Review on Hybrid Deep Learning Models for Enhancing Encryption Techniques Against Side Channel Attacks
by: Amjed A. Ahmed, et al.
Published: (2024-01-01) -
On the performance of non‐profiled side channel attacks based on deep learning techniques
by: Ngoc‐Tuan Do, et al.
Published: (2023-05-01) -
Resilience evaluation of memristor based PUF against machine learning attacks
by: Hebatallah M. Ibrahim, et al.
Published: (2024-10-01) -
Evaluating the Vulnerability of Hiding Techniques in Cyber-Physical Systems Against Deep Learning-Based Side-Channel Attacks
by: Seungun Park, et al.
Published: (2025-06-01)