zkFL: Zero-Knowledge Proof-based Gradient Aggregation for Federated Learning

arXiv:2310.02554v4 Announce Type: replace-cross
Abstract: Federated learning (FL) is a machine learning paradigm, which enables multiple and decentralized clients to collaboratively train a model under the orchestration of a central aggregator. FL can be a scalable machine learning solution in big data scenarios. Traditional FL relies on the trust assumption of the central aggregator, which forms cohorts of clients honestly. However, a malicious aggregator, in reality, could abandon and replace the client's training models, or insert fake clients, to manipulate …

aggregation arxiv big big data can clients cs.ai cs.cr cs.lg data decentralized federated federated learning knowledge machine machine learning orchestration paradigm proof solution train trust under