TFL-DT: A Trust Evaluation Scheme for Federated Learning in Digital Twin for Mobile Networks

Guo, Jingjing; Liu, Zhiquan; Tian, Siyi; Huang, Feiran; Li, Jiaxing; Li, Xinghua; Kostromitin, Konstantin Igorevich; Ma, Jianfeng

doi:10.1109/jsac.2023.3310094

articleIEEE Journal on Selected Areas in CommunicationsAug 30, 2023HYBRID OA

TFL-DT: A Trust Evaluation Scheme for Federated Learning in Digital Twin for Mobile Networks

JGJingjing Guo ZLZhiquan Liu STSiyi Tian FHFeiran Huang JLJiaxing Li

Xidian University · Jinan University · +1 more institution

Indexed incrossref

Abstract

Due to the distributed collaboration and privacy protection features, federated learning is a promising technology to perform the model training in virtual twins of Digital Twin for Mobile Networks (DTMN). In order to enhance the reliability of the model, it is always expected that the users involved in federated learning have trustworthy behaviors. Yet, available trust evaluation schemes for federated learning have the problems of considering simplex evaluation factor and using coarse-grained trust calculation method. In this paper, we propose a trust evaluation scheme for federated learning in DTMN, which takes direct trust evidence and recommended trust information into account. A user behavior model is…

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Topics

Keywords

Computer science
Scheme (mathematics)
Computer network
Human–computer interaction

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