Privacy-Preserving and Poisoning-Robust Federated Learning for Industrial IoT
A hierarchical privacy protection and poisoning-robust defense framework for industrial federated learning is proposed and can effectively suppress global-model degradation under multiple poisoning attacks and achieves a favorable balance among privacy protection strength, robustness, and training efficiency.