A polynomial proxy model approach to verifiable decentralized federated learning

Abstract Decentralized Federated Learning improves data privacy and eliminates single points of failure by removing reliance on centralized storage and model aggregation in distributed computing systems. Ensuring the integrity of computations during local model training is a significant challenge, e...

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Bibliographic Details

Published in:	Scientific Reports
Main Authors:	Tan Li, Samuel Cheng, Tak Lam Chan, Haibo Hu
Format:	Article
Language:	English
Published:	Nature Portfolio 2024-11-01
Subjects:	Zero knowledge proof Computation integrity Decentralized federate learning
Online Access:	https://doi.org/10.1038/s41598-024-79798-x