RDTSM: Robust Defense Based on Trusted Shadow Model Against Poisoning Attacks for Federated Learning
Federated learning enables collaborative model training without sharing raw data, but remains vulnerable to poisoning attacks from malicious clients. These adversarial participants craft harmful updates to degrade global model performance or induce targeted misclassification. Without trusted reference gradients, the ce...