2 papers
cs.CV2025
Towards Powerful and Practical Patch Attacks for 2D Object Detection in Autonomous Driving
Yuxin Cao, Yedi Zhang, Wentao He +5
Learning-based autonomous driving systems remain critically vulnerable to adversarial patches, posing serious safety and security risks in their real-world deployment. Black-box at…
cs.CR2025
Towards Stealthy and Effective Backdoor Attacks on Lane Detection: A Naturalistic Data Poisoning Approach
Yifan Liao, Yuxin Cao, Yedi Zhang +5
Deep learning-based lane detection (LD) plays a critical role in autonomous driving and advanced driver assistance systems. However, its vulnerability to backdoor attacks presents…