Ke-Qian Liu

Privacy-Preserving and Byzantine-Robust Federated Learning With Mean-Constrained Secret Sharing

Federated learning faces three critical challenges in enabling cross-institutional collaboration: privacy leakage, poisoning by malicious clients, and unverifiable aggregation results. To address these issues in a unified manner, we propose PVeriFL—a federated learning framework that integrates privacy preservation, By...