6 papers
TRACE: Data-Free Text Reconstruction Attacks against Approximate Unlearning in LLMs
Mengying Zhang, Derui Wang, Ibrahim Khalil +3
As large language models (LLMs) face growing demands for data removal driven by regulatory compliance, copyright concerns, and privacy protection, approximate unlearning has emerge…
WinFLoRA: Incentivizing Client-Adaptive Aggregation in Federated LoRA under Privacy Heterogeneity
Mengsha Kou, Xiaoyu Xia, Ziqi Wang +4
Large Language Models (LLMs) increasingly underpin intelligent web applications, from chatbots to search and recommendation, where efficient specialization is essential. Low-Rank A…
LocalStyleFool: Regional Video Style Transfer Attack Using Segment Anything Model
Yuxin Cao, Jinghao Li, Xi Xiao +5
Previous work has shown that well-crafted adversarial perturbations can threaten the security of video recognition systems. Attackers can invade such models with a low query budget…
Reinforcement Unlearning
Dayong Ye, Tianqing Zhu, Congcong Zhu +6
Machine unlearning refers to the process of mitigating the influence of specific training data on machine learning models based on removal requests from data owners. However, one i…
LogoStyleFool: Vitiating Video Recognition Systems via Logo Style Transfer
Yuxin Cao, Ziyu Zhao, Xi Xiao +3
Video recognition systems are vulnerable to adversarial examples. Recent studies show that style transfer-based and patch-based unrestricted perturbations can effectively improve a…
Flow-Attention-based Spatio-Temporal Aggregation Network for 3D Mask Detection
Yuxin Cao, Yian Li, Yumeng Zhu +2
Anti-spoofing detection has become a necessity for face recognition systems due to the security threat posed by spoofing attacks. Despite great success in traditional attacks, most…