Towards Defending against Adversarial Examples via Attack-Invariant Features

Dawei Zhou, Tongliang Liu, Bo Han +3

Deep neural networks (DNNs) are vulnerable to adversarial noise. Their adversarial robustness can be improved by exploiting adversarial examples. However, given the continuously ev…