2 papers
cs.CR2024
A Learning-Based Attack Framework to Break SOTA Poisoning Defenses in Federated Learning
Yuxin Yang, Qiang Li, Chenfei Nie +3
Federated Learning (FL) is a novel client-server distributed learning framework that can protect data privacy. However, recent works show that FL is vulnerable to poisoning attacks…
cs.CR2024
Distributed Backdoor Attacks on Federated Graph Learning and Certified Defenses
Yuxin Yang, Qiang Li, Jinyuan Jia +2
Federated graph learning (FedGL) is an emerging federated learning (FL) framework that extends FL to learn graph data from diverse sources. FL for non-graph data has shown to be vu…