Improving the Transferability of Adversarial Examples by Feature
Augmentation
Improving the Transferability of Adversarial Examples by Feature
Augmentation
Despite the success of input transformation-based attacks on boosting adversarial transferability, the performance is unsatisfying due to the ignorance of the discrepancy across models. In this paper, we propose a simple but effective feature augmentation attack (FAUG) method, which improves adversarial transferability without introducing extra computation costs. Specifically, we inject …