3 papers
cs.CV2023
Generating Visually Realistic Adversarial Patch
Xiaosen Wang, Kunyu Wang
Deep neural networks (DNNs) are vulnerable to various types of adversarial examples, bringing huge threats to security-critical applications. Among these, adversarial patches have…
cs.CV2023
LFAA: Crafting Transferable Targeted Adversarial Examples with Low-Frequency Perturbations
Kunyu Wang, Juluan Shi, Wenxuan Wang
Deep neural networks are susceptible to adversarial attacks, which pose a significant threat to their security and reliability in real-world applications. The most notable adversar…
cs.CV2023
Boosting Adversarial Transferability by Block Shuffle and Rotation
Kunyu Wang, Xuanran He, Wenxuan Wang +1
Adversarial examples mislead deep neural networks with imperceptible perturbations and have brought significant threats to deep learning. An important aspect is their transferabili…