Chinese Journal of Network and Information Security ›› 2021, Vol. 7 ›› Issue (6): 99-112.doi: 10.11959/j.issn.2096-109x.2021083

Special Issue: 联邦学习 区块链

• TopicⅡ: Blockchain Technology • Previous Articles     Next Articles

Federated learning scheme for mobile network based on reputation evaluation mechanism and blockchain

Ming YANG1, Xuexian HU1, Qihui ZHANG1, Jianghong WEI1, Wenfen LIU2   

  1. 1 Strategic Support Force Information Engineering University, Zhengzhou 450001, China
    2 Guilin University of Electronic Technology, Guilin 541004, China
  • Revised:2021-03-30 Online:2021-12-15 Published:2021-12-01
  • Supported by:
    TheNational Natural Science Foundation of China(62172433);TheNational Natural Science Foundation of China(62172434);TheNational Natural Science Foundation of China(61862011);TheNational Natural Science Foundation of China(61872449);Guangxi Key Laboratory of Cryptography and Information Security(GCIS201704)

Abstract:

Federated learning is a new distributed machine learning technology, where training tasks are deployed on user side and training model parameters are sent to the server side.In the whole process, participants do not need to share their own data directly, which greatly avoids privacy issues.However, the trust relationship between mobile users in the learning model has not been established in advance, there is hidden safety when users perform cooperative train with each other.In view of the above problems, a federated learning scheme for mobile network based on reputation evaluation mechanism and blockchain was proposed.The scheme allowed the server side to use subjective logic models to evaluate the reputation of participating mobile users and provided them with credible reputation opinions sharing environment and dynamic access strategy interface based on the technique of smart contract of blockchain.Theoretical and experimental analys is results show that the scheme can enable the server side to select reliable users for training.And it can achieve more fair and effective reputation calculations, which improves the accuracy of federated learning.

Key words: mobile network, federated learning, blockchain, reputation management

CLC Number: 

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