5 papers · 1 filter
GDBR: Label Recovery Attack Against Partial Gradient Encryption in Federated Learning
Rui Zhang, Ka-Ho Chow
The increasing demand for data privacy, alongside the benefits of aggregating data from networked devices, has catalyzed the emergence of federated learning (FL). In FL, clients jo…
OCR Hinders RAG: Evaluating the Cascading Impact of OCR on Retrieval-Augmented Generation
Junyuan Zhang, Qintong Zhang, Bin Wang +6
Retrieval-augmented Generation (RAG) enhances Large Language Models (LLMs) by integrating external knowledge to reduce hallucinations and incorporate up-to-date information without…
Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning
Junjie Shan, Ziqi Zhao, Jialin Lu +3
Foundation models that bridge vision and language have made significant progress. While they have inspired many life-enriching applications, their potential for abuse in creating n…
AnywhereDoor: Multi-Target Backdoor Attacks on Object Detection
Jialin Lu, Junjie Shan, Ziqi Zhao +1
As object detection becomes integral to many safety-critical applications, understanding its vulnerabilities is essential. Backdoor attacks, in particular, pose a serious threat by…
Harmless Backdoor-based Client-side Watermarking in Federated Learning
Kaijing Luo, Ka-Ho Chow
Protecting intellectual property (IP) in federated learning (FL) is increasingly important as clients contribute proprietary data to collaboratively train models. Model watermarkin…