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

• Published in: IEEE transactions on industrial informatics Vol. 18; no. 12; pp. 8864 - 8875
• Main Authors: Yang, Liu, Yu, Keping, Yang, Simon X., Chakraborty, Chinmay, Lu, Yinzhi, Guo, Tan
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.12.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G edge computing; 5G mobile communication; Cloud computing; Clustering; device-to-device (D2D) communication; Edge computing; Health services; Informatics; Internet of medical things; Internet of Medical Things (IoMT); security; Training; trust cloud; Trust management; Trustworthiness; Wireless communication; Wireless sensor networks
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2021.3128954

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.