Defense against Backdoor Attacks via Identifying and Purifying Bad Neurons. (arXiv:2208.06537v1 [cs.LG])

The opacity of neural networks leads their vulnerability to backdoor attacks,
where hidden attention of infected neurons is triggered to override normal
predictions to the attacker-chosen ones. In this paper, we propose a novel
backdoor defense method to mark and purify the infected neurons in the
backdoored neural networks. Specifically, we first define a new metric, called
benign salience. By combining the first-order gradient to retain the
connections between neurons, benign salience can identify the infected neurons
with higher accuracy …

attacks backdoor bad defense lg