FLTG: Byzantine-Robust Federated Learning Via Angle-Based Defense and Non-IID-Aware Weighting

Byzantine attacks during model aggregation in Federated Learning FL threaten training integrity by manipulating malicious clients' updates. Existing methods struggle with limited robustness under high malicious client ratios and sensitivity to non-i.i.d. data, leading to degraded accuracy. To...