Rongyi Zhu, Zeliang Zhang, Susan Liang, Zhuo Liu, Chenliang Xu
TL;DR通过学习选择最佳的变换组合以提高对抗传递能力的一种新方法,名为Learning to Transform (L2T),在实验中展现出优于现有方法的性能,并证实其有效性和实用意义。
Abstract
adversarial examples, crafted by adding perturbations imperceptible to humans, can deceive neural networks. Recent studies identify the adversarial transferability across various models, \textit{i.e.}, the cross-