4.8 Article

An Intelligent Trust Cloud Management Method for Secure Clustering in 5G Enabled Internet of Medical Things

期刊

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 18, 期 12, 页码 8864-8875

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2021.3128954

关键词

Cloud computing; Wireless sensor networks; Trust management; Informatics; 5G mobile communication; Wireless communication; Training; 5G edge computing; device-to-device (D2D) communication; Internet of Medical Things (IoMT); security; trust cloud

资金

  1. National Natural Science Foundation of China [61801072]
  2. Science and Technology Research Program of Chongqing Municipal Education Commission [KJQN202000641]
  3. Natural Science Foundation of Chongqing [cstc2020jcyj-msxmX0636]
  4. Japan Society for the Promotion of Science [JP18K18044, JP21K17736]

向作者/读者索取更多资源

This article presents an intelligent trust cloud management method for secure and reliable communication in 5G edge computing and device-to-device enabled Internet of Medical Things (IoMT) systems. The method includes constructing standard trust clouds, establishing individual trust clouds, proposing a trust classification scheme, and implementing a trust cloud update mechanism. Simulation results show that this method effectively addresses trust uncertainty and improves the detection accuracy of malicious devices.
5G edge computing enabled Internet of Medical Things (IoMT) is an efficient technology to provide decentralized medical services while device-to-device (D2D) communication is a promising paradigm for future 5G networks. To assure secure and reliable communication in 5G edge computing and D2D enabled IoMT systems, this article presents an intelligent trust cloud management method. First, an active training mechanism is proposed to construct the standard trust clouds. Second, individual trust clouds of the IoMT devices can be established through fuzzy trust inferring and recommending. Third, a trust classification scheme is proposed to determine whether an IoMT device is malicious. Finally, a trust cloud update mechanism is presented to make the proposed trust management method adaptive and intelligent under an open wireless medium. Simulation results demonstrate that the proposed method can effectively address the trust uncertainty issue and improve the detection accuracy of malicious devices.

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