The curse of class imbalance and conflicting metrics with machine learning for side-channel evaluations

• Main Authors: Picek, Stjepan, Heuser, Annelie, Jovic, Alan, Bhasin, Shivam, Regazzoni, Francesco
• Other Authors: Temasek Laboratories @ NTU
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Computer science and engineering; Profiled Side-Channel Attacks; Imbalanced Datasets
• Online Access: https://hdl.handle.net/10356/160593
• Institution: Nanyang Technological University

We concentrate on machine learning techniques used for profiled side-channel analysis in the presence of imbalanced data. Such scenarios are realistic and often occurring, for instance in the Hamming weight or Hamming distance leakage models. In order to deal with the imbalanced data, we use various...