Optimizing cryptographic protocols against side channel attacks using WGAN-GP and genetic algorithms
Abstract This research introduces a novel hybrid cryptographic framework that combines traditional cryptographic protocols with advanced methodologies, specifically Wasserstein Generative Adversarial Networks with Gradient Penalty (WGAN-GP) and Genetic Algorithms (GA). We evaluated several cryptogra...
Saved in:
| Main Authors: | Purushottam Singh, Prashant Pranav, Sandip Dutta |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-86118-4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Attention-Guided Wireless Channel Modeling and Generating
by: Yawen He, et al.
Published: (2025-03-01) -
Defense Method for Smart Grid GPS Spoofing Attack Based on BiLSTM and Self-attention Mechanism Generative Adversarial Network
by: Hui WU, et al.
Published: (2024-09-01) -
Trace Copilot: Automatically Locating Cryptographic Operations in Side-Channel Traces by Firmware Binary Instrumenting
by: Shipei Qu, et al.
Published: (2024-12-01) -
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) -
Platelets Image Classification Through Data Augmentation: A Comparative Study of Traditional Imaging Augmentation and GAN-Based Synthetic Data Generation Techniques Using CNNs
by: Itunuoluwa Abidoye, et al.
Published: (2025-06-01)