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

TL;DR

This paper introduces an intelligent trust cloud management approach for secure and reliable communication in 5G-enabled Internet of Medical Things, enhancing trust assessment and malicious device detection.

Contribution

It proposes a novel trust management framework with active training, fuzzy trust inference, and adaptive updates tailored for 5G IoMT systems.

Findings

Improves malicious device detection accuracy

Effectively addresses trust uncertainty issues

Enhances security in 5G IoMT communications

Abstract

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 paper presents an intelligent trust cloud management method. Firstly, an active training mechanism is proposed to construct the standard trust clouds. Secondly, individual trust clouds of the IoMT devices can be established through fuzzy trust inferring and recommending. Thirdly, 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.