#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