An intelligent and privacy-enhanced data sharing strategy for blockchain-empowered Internet of Things

作     者：Qinyang Miao Hui Lin Jia Hu Xiaoding Wang 

作者机构：College of Computer and Cyber SecurityFujian Normal UniversityFuzhou350117China Engineering Research Center of Cyber Security and Education InformatizationFujian Province UniversityFuzhou350117China University of ExeterEX44RN ExeterUK 

出 版 物：《Digital Communications and Networks》 (数字通信与网络（英文版）)

年 卷 期：2022年第8卷第5期

页      面：636-643页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 

基　　金：This work is supported by National Natural Science Foundation of China under Grant No.U1905211 and 61702103 Natural Science Foundation of Fujian Province under Grant No.2020J01167 and 2020J01169 

主　　题：Data sharing Federated learning Blockchain Privacy protection IoT 

摘      要：With the development of the Internet of Things(IoT),the massive data sharing between IoT devices improves the Quality of Service(QoS)and user experience in various IoT ***,data sharing may cause serious privacy leakages to data *** address this problem,in this study,data sharing is realized through model sharing,based on which a secure data sharing mechanism,called BP2P-FL,is proposed using peer-to-peer federated learning with the privacy protection of data *** addition,by introducing the blockchain to the data sharing,every training process is recorded to ensure that data providers offer high-quality *** further privacy protection,the differential privacy technology is used to disturb the global data sharing *** experimental results show that BP2P-FL has high accuracy and feasibility in the data sharing of various IoT applications.