230 citations · 376 across the 34 of their papers we have counts for
4 papers · 2 filters
Sampling-based Fast Gradient Rescaling Method for Highly Transferable Adversarial Attacks
Xu Han, Anmin Liu, Chenxuan Yao +2
Deep neural networks are known to be vulnerable to adversarial examples crafted by adding human-imperceptible perturbations to the benign input. After achieving nearly 100% attack…
Rethinking the Backward Propagation for Adversarial Transferability
Xiaosen Wang, Kangheng Tong, Kun He
Transfer-based attacks generate adversarial examples on the surrogate model, which can mislead other black-box models without access, making it promising to attack real-world appli…
PIAT: Parameter Interpolation based Adversarial Training for Image Classification
Kun He, Xin Liu, Yichen Yang +4
Adversarial training has been demonstrated to be the most effective approach to defend against adversarial attacks. However, existing adversarial training methods show apparent osc…
Semantic Adversarial Attacks on Face Recognition through Significant Attributes
Yasmeen M. Khedr, Yifeng Xiong, Kun He
Face recognition is known to be vulnerable to adversarial face images. Existing works craft face adversarial images by indiscriminately changing a single attribute without being aw…