FL with homomorphic encryption matches centralized ML performance for CVD risk prediction but adds cryptographic overhead, while DP-FL has lower cost yet greater accuracy loss especially for logistic regression.
InProceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2621–2635 (2023)
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Privacy-Preserving Federated Learning via Differential Privacy and Homomorphic Encryption for Cardiovascular Disease Risk Modeling
FL with homomorphic encryption matches centralized ML performance for CVD risk prediction but adds cryptographic overhead, while DP-FL has lower cost yet greater accuracy loss especially for logistic regression.