Federated Learning with Blockchain for Privacy-Preserving Data Sharing in Internet of Vehicles  

作　　者：Wenxian Jiang Mengjuan Chen Jun Tao 

机构地区：[1]School of Cyber Science and Engineering,Southeast University,Nanjing 211189,China [2]College of Computer Science and Technology,Huaqiao University,Xiamen 361021,China [3]Key Lab of CNII,MOE,Southeast University,Nanjing 211189,China [4]Purple Mountain Laboratories:Networking Communications and Security,Nanjing 211111,China

出　　处：《China Communications》2023年第3期69-85,共17页中国通信（英文版）

基　　金：supported by the Ministry of Education Industry-University Cooperation Collaborative Education Projects of China under Grant 202102119036 and 202102082013。

摘　　要：Data sharing technology in Internet of Vehicles(Io V)has attracted great research interest with the goal of realizing intelligent transportation and traffic management.Meanwhile,the main concerns have been raised about the security and privacy of vehicle data.The mobility and real-time characteristics of vehicle data make data sharing more difficult in Io V.The emergence of blockchain and federated learning brings new directions.In this paper,a data-sharing model that combines blockchain and federated learning is proposed to solve the security and privacy problems of data sharing in Io V.First,we use federated learning to share data instead of exposing actual data and propose an adaptive differential privacy scheme to further balance the privacy and availability of data.Then,we integrate the verification scheme into the consensus process,so that the consensus computation can filter out low-quality models.Experimental data shows that our data-sharing model can better balance the relationship between data availability and privacy,and also has enhanced security.

关 键 词：blockchain federated learning PRIVACY data sharing Internet of Vehicles 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]