Xuanhui Zhong

Improving Adversarial Transferability with Local Perturbation Augmentation

Adversarial examples expose fundamental vulnerabilities within deep neural networks, and their transferability highlights shared weaknesses across diverse models. Existing mainstream attack methods often rely on iterative processes with various strategies to improve transferability, but the limited