2 papers
cs.CR2024
Efficient Byzantine-Robust and Provably Privacy-Preserving Federated Learning
Chenfei Nie, Qiang Li, Yuxin Yang +2
Federated learning (FL) is an emerging distributed learning paradigm without sharing participating clients' private data. However, existing works show that FL is vulnerable to both…
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…