Eliminating Backdoor Triggers for Deep Neural Networks Using Attention Relation Graph Distillation

1 code implementation • 21 Apr 2022 • Jun Xia, Ting Wang, Jiepin Ding, Xian Wei, Mingsong Chen

Due to the prosperity of Artificial Intelligence (AI) techniques, more and more backdoors are designed by adversaries to attack Deep Neural Networks (DNNs). Although the state-of-the-art method Neural Attention Distillation (NAD) can effectively erase backdoor triggers from DNNs, it still suffers from non-negligible Attack Success Rate (ASR) together with lowered classification ACCuracy (ACC), since NAD focuses on backdoor defense using attention features (i. e., attention maps) of the same order.

backdoor defense Knowledge Distillation +1