30 papers
Imperceptible and Reversible Adversarial Examples against Vision-Language Models for Privacy Protection
Qi Lu, Ziqi Zhou, Yufei Song +5
Vision Language Models (VLMs) offer powerful multimodal ability but also expose users to text-based privacy attacks where adversaries crawl online photos and query VLMs to extract…
VFACamou: View-Fused Adversarial Camouflage for Environment-Adaptive Physical Evasion
Shihui Yan, Hu Liu, Junyu Shi +6
Adversarial camouflage in the physical world remains highly challenging, particularly under UAV reconnaissance where targets undergo continuous geometric changes and extreme illumi…
Defending Jailbreak Attacks on Large Language Models via Manifold Trajectory Kinetics
Hangtao Zhang, Yucheng Zhao, Sishun Liu +8
Jailbreak prompts can bypass alignment guardrails in large language models (LLMs) and elicit unsafe outputs, making reliable deployment-time detection critical. Prior detection app…
Transferable Physical-World Adversarial Patches Against Object Detection in Autonomous Driving
Zihui Zhu, Ziqi Zhou, Yichen Wang +3
Deep learning drives major advances in autonomous driving (AD), where object detectors are central to perception. However, adversarial attacks pose significant threats to the relia…
Transferable Physical-World Adversarial Patches Against Pedestrian Detection Models
Shihui Yan, Ziqi Zhou, Yufei Song +3
Physical adversarial patch attacks critically threaten pedestrian detection, causing surveillance and autonomous driving systems to miss pedestrians and creating severe safety risk…
Visual Adversarial Attack on Vision-Language Models for Autonomous Driving
Tianyuan Zhang, Lu Wang, Xinwei Zhang +7
Vision-language models (VLMs) have significantly advanced autonomous driving (AD) by enhancing reasoning capabilities. However, these models remain highly vulnerable to adversarial…