HADES selectively encrypts privacy-sensitive features identified by PCA in federated learning, trains hybrid encrypted and plaintext networks, and fuses them to match vanilla FL accuracy with reduced overhead and better privacy.
Privacy preserving pca for multiparty modeling,
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HADES: Privacy-Preserving Federated Learning via Selective Feature Encryption and Hybrid Model Fusion
HADES selectively encrypts privacy-sensitive features identified by PCA in federated learning, trains hybrid encrypted and plaintext networks, and fuses them to match vanilla FL accuracy with reduced overhead and better privacy.