期刊
IEEE INTERNET OF THINGS JOURNAL
卷 8, 期 21, 页码 15672-15682出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2020.3029221
关键词
Medical services; Reliability; Internet of Things; Monitoring; Sensors; Artificial neural network; efficient healthcare; integrity; Internet of Medical Things (IoMT); trust management
资金
- Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia [IFKSURG-1437-035]
Internet of Medical Things (IoMT) provides a diverse platform that improves healthcare accuracy, reliability, and efficiency, but also faces security challenges. By utilizing trust parameters and lightweight encryption mechanisms, a secure network can be maintained with enhanced security and integrity during data dissemination.
Internet of Medical Things (IoMT) provides a diverse platform for healthcare to enhance the accuracy, reliability, and efficiency. In addition, it utilizes the productivity of available equipment to improve patients' health. IoMT also provides distinct ways by which healthcare will be revolutionized as it provides numerous opportunities to handle operations with precision. However, numerous advantages have raised several security challenges, such as trust, data integrity, network constraints, and real-time processing among others. There is a requirement for a robust approach to maintain data integrity along with the behavior detection of nodes to completely maintain a secure environment. In the proposed approach, the mechanism is capable of maintaining a robust network by predicting and eliminating malicious nodes. The proposed NeuroTrust approach utilizes the trust parameters to evaluate the degree of trust that include reliability, compatibility, and packet delivery. This approach also lightens the two-way computation burden and uses a lightweight encryption mechanism to further enhance the security and integrity during data dissemination, which is required for the digital revolution in delivering efficient high quality healthcare. The performance of the proposed approach has been extensively evaluated against the absolute trust formulation, accuracy of trust computation, energy consumption, and several potential attacks. The simulation results show the effective performance to identify malicious and compromised nodes, and maintain resilience against various attacks.
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