A comparative study shows CNNs, ResNets, and feature-selected Random Forests can recover an AES key byte from ASCAD EM traces despite near-zero classification accuracy, when evaluated with the domain-specific Key Rank metric.
In: Advances in Cryptology—CRYPTO’99: 19th Annual International Cryptology Confer- ence Santa Barbara, California, USA, August 15–19, 1999 Proceedings 19
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Machine Learning-Based AES Key Recovery via Side-Channel Analysis on the ASCAD Dataset
A comparative study shows CNNs, ResNets, and feature-selected Random Forests can recover an AES key byte from ASCAD EM traces despite near-zero classification accuracy, when evaluated with the domain-specific Key Rank metric.