3 papers
cs.CV2025
Enabling Heterogeneous Adversarial Transferability via Feature Permutation Attacks
Tao Wu, Tie Luo
Adversarial attacks in black-box settings are highly practical, with transfer-based attacks being the most effective at generating adversarial examples (AEs) that transfer from sur…
cs.LG2024
LRS: Enhancing Adversarial Transferability through Lipschitz Regularized Surrogate
Tao Wu, Tie Luo, Donald C. Wunsch
The transferability of adversarial examples is of central importance to transfer-based black-box adversarial attacks. Previous works for generating transferable adversarial example…
cs.LG2023
CR-SAM: Curvature Regularized Sharpness-Aware Minimization
Tao Wu, Tie Luo, Donald C. Wunsch
The capacity to generalize to future unseen data stands as one of the utmost crucial attributes of deep neural networks. Sharpness-Aware Minimization (SAM) aims to enhance the gene…