arXiv Machine Learning October 5, 2026 By Dominik Roy George, Varesh Mishra, Aysajan Abidin

PoCoFL: POlicy-COmpliant Federated Learning

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PoCoFL is a federated learning framework that separates the type of FL, policy semantics, and cryptographic realization to ensure policy compliance. It formalizes client and aggregation requirements as policy-dependent relations, allowing clients to prove compliance with commitments and zero-knowledge proofs, and aggregators to prove correct processing of admitted contributions. The paper demonstrates PoCoFL through four instantiations—vanilla, continual, personalized, and threshold-encrypted FL—showing its versatility and practical feasibility across different learning objectives.

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