4 papers
Fast and Lightweight Backdoor Detection via Head Random Probing
Yinbo Yu, Xueyu Yin, Jing Fang +4
Deep neural networks (DNNs) remain critically vulnerable to backdoor attacks. Existing post-training detectors often require clean or surrogate data, gradients, or iterative trigge…
Lightweight and Fast Backdoor Model Detection
Yinbo Yu, Jing Fang, Xuewen Zhang +4
Deep neural networks (DNN), despite their remarkable performance, are highly vulnerable to backdoor attacks. Existing defenses mainly rely on activation anomaly analysis or trigger…
AdaClearGrasp: Learning Adaptive Clearing for Zero-Shot Robust Dexterous Grasping in Densely Cluttered Environments
Zixuan Chen, Wenquan Zhang, Jing Fang +7
In densely cluttered environments, physical interference, visual occlusions, and unstable contacts often cause direct dexterous grasping to fail, while aggressive singulation strat…
BLAST: A Stealthy Backdoor Leverage Attack against Cooperative Multi-Agent Deep Reinforcement Learning based Systems
Jing Fang, Saihao Yan, Xueyu Yin +3
Recent studies have shown that cooperative multi-agent deep reinforcement learning (c-MADRL) is under the threat of backdoor attacks. Once a backdoor trigger is observed, it will p…