Author

J. Fahs

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#machine learning May 2026

Privacy-Enhanced Zero-Order Federated Learning via xMK-CKKS over Wireless Channels

This work proposes a four-phase protocol that enables the aggregation of xMK-CKKS over a shared wireless channel without channel estimation and shows that the residual noise induced by encryption and wireless aggregation preserves the standard convergence rate up to a negligible noise floor.

Anthony Ayli, K. Harris, J. Fahs et al. · arXiv.org · 0 citations