Secure Aggregation for Privacy-Preserving Federated Learning on Clinical EEG Data
A privacy-preserving federated learning framework for clinical EEG data that uses masking-based secure aggregation as its core protection mechanism that remains compatible with federated model training, although malicious-setting safeguards and lightweight consistency-checking mechanisms introduce additional computatio...