arXiv Machine Learning June 9, 2026 By Anthony Ayli, Khalil Harris, Jihad Fahs, Mohamad Assaad

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

Read the original on arXiv Machine Learning →

arXiv:2605. 30123v2 Announce Type: replace-cross Abstract: Homomorphic encryption (HE) enables privacy-preserving aggregation in federated learning (FL) by allowing the server to operate on encrypted data without decryption.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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