Deep learning-based side-channel analysis: exploiting vulnerabilities and explaining neural network decisions

• 主要作者: Yap, Trevor Hong Eng
• 其他作者: Thomas Peyrin
• 格式: Thesis-Doctor of Philosophy
• 語言: English
• 出版: Nanyang Technological University 2025
• 主題: Mathematical Sciences; Deep learning; Side-channel analysis; Interpretability; Explainability; Artificial trace generation; Hyperparameters tuning
• 在線閱讀: https://hdl.handle.net/10356/183421
• 機構: Nanyang Technological University

Side-channel analysis first dates back to the 1960s and has gained popularity ever since 1996 when Paul Kocher published a paper introducing the concept of timing attacks [1]. Subsequently, various physical leakages such as power consumption [2] and electromagnetic emanation [3] were exploited to...