MASTER Assignment
Weighted, Weighted and Art Found Wanting: A Complexity- minimisation Approach for Neuroevolution-based Side-channel Analysis
Type : Master M-CS
Period: August, 2024 - January, 2025
Student : Velde, van der P. (Peter, Student M-CS)
Date Final project: January 27, 2025
Supervisors:
Abstract:
Currently the state of the art in Side-Channel Analysis in the sphere of cryptography is to analyze them using Deep Neural Networks (DNN). A common problem in this field is to minimize both the number of traces required to reach a good classification performance and the number of trainable parameters of the DNN. Recently a neuroevolution approach was researched as a possible solution to this problem called NASCTY. With this research project we hope to discover a number of possible improvements to the current system hoping to overcome some of its deficits and problems. This includes looking at a custom fitness function to reduce complexity and the use of different anti-premature convergence strategies.