Lightweight and Fast Backdoor Model Detection

ArXi:2605.18907v1 Announce Type: cross Deep neural networks (DNN), despite their remarkable performance, are highly vulnerable to backdoor attacks. Existing defenses mainly rely on activation anomaly analysis or trigger reverse engineering and often require clean samples or prior knowledge of trigger patterns, resulting in limited efficacy, practicability, and generalizability. critically, while advanced attacks can implement backdoor implantation in milliseconds, current detection approaches typically demand minutes or even hours.