VPPFL: Verifiable Privacy-Preserving Federated Learning in Cloud Environment

As a distributed machine learning paradigm, federated learning has attracted wide attention from academia and industry by enabling multiple users to jointly train models without sharing local data. However, federated learning still faces various security and privacy issues. First, even if users only...

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Bibliografski detalji

Glavni autori:	Huiyong Wang, Tengfei Yang, Yong Ding, Shijie Tang, Yujue Wang
Format:	Artigo
Jezik:	Inglês
Izdano:	IEEE 2024-01-01
Serija:	IEEE Access
Teme:	Privacy protection federated learning verifiable threshold multi-key homomorphic encryption
Online pristup:	https://ieeexplore.ieee.org/document/10703046/
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