Preprint
Oct 2026
Combining Homomorphic Encryption and Differential Privacy in Federated Learning for Model Inspection and Availability
The increasing prevalence of decentralized data has led to a growing interest in federated learning, which enables collaborative model training without clients sharing their sensitive local data. However, FL alone does not sufficiently protect sensitive training data and is generally coupled with privacy-preserving tec...
Ceren Yildirim, K. Kaya, S. Yıldırım et al.
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