L-RTAM: Logarithm based reliable trust assessment model for WBSNs

Abstract

In has been considered that the sensor network’s safety measures have been built upon a non-realistic, trusted environment. After analyzing the trust models for wireless body sensor networks (WBSNs), it has been found that trust models should be distributed, lightweight, and robust against various vulnerabilities. They are also facing issues regarding computation overhead. Moreover, there is a threat of internal attacks over WBSNs. These attacks may be an on-off attack, data modification, message disclosure, collusion attack, bad-mouthing, brute force, and denial of service attack. Thus, this research paper considers three issues: network internal security, resource management, and spiteful node detection. The Proposed dynamic and trustworthy lightweight trust assessment scheme (RTAM) for WBSNs would play a significant role in the appropriate usage of resources and minimize the computational overhead. RTAM is a scalable trust model that incorporates logarithm based direct trust, indirect trust, and success ratio based data trust. It would be safe from a different type of attacks. To check the malicious activities that have been performed in nodes, some malicious nodes from the total nodes have been managed by the proposed network.