ZMASA: Robust Aggregation for Federated Learning Against Byzantine Attacks.
Federated learning (FL) enables collaborative model training without sharing raw data, but its robustness is vulnerable to Byzantine clients, especially under non-identically distributed (non-IID) data. In heterogeneous FL, benign client updates may become multimodal and statistically diverse, making it difficult for m...