Skip to content

The classifier judged this item not relevant to AI security, so it is left out of lists, feeds, the API and dataset releases. If that is wrong, report a correction on this page.

InfoResearchPeer-reviewed

FreeFL: Privacy-Preserving Cross-Silo Federated Learning Without Third Party

Published
Record updated

Summary

FreeFL is a cross-silo federated learning protocol that removes the need for a trusted third party and a centralized aggregator. It replaces homomorphic encryption with a lightweight decentralized symmetric encryption scheme with additive homomorphism, built from a decentralized multiparty symmetric encryption (DMSE) scheme and two multiparty computation protocols. The authors report high computation and communication efficiency and significant computational gains over existing HE-based cross-silo FL protocols.