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Weighted, Weighted and Art Found Wanting: A Complexity-minimisation Approach for Neuroevolution-based Side-channel Analysis

Velde, Peter van der (2025) Weighted, Weighted and Art Found Wanting: A Complexity-minimisation Approach for Neuroevolution-based Side-channel Analysis.

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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.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Computer Science MSc (60300)
Link to this item:https://purl.utwente.nl/essays/105017
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