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

• المؤلف الرئيسي: Yap, Trevor Hong Eng
• مؤلفون آخرون: Thomas Peyrin
• التنسيق: Thesis-Doctor of Philosophy
• اللغة: English
• منشور في: Nanyang Technological University 2025
• الموضوعات: Mathematical Sciences; Deep learning; Side-channel analysis; Interpretability; Explainability; Artificial trace generation; Hyperparameters tuning
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/183421

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...