The rapid development of smart devices and the consequent demand their reliability have posed many challenges limiting their versatility. One of the most significant challenges is safeguarding the widespread network of sensors and devices within harsh remote environments. Numerous trust schemes have been proposed to overcome related IoT security concerns. However, most of these schemes are not lightweight and consequently are not energy-efficient. This paper proposes a reliable lightweight trust evaluation scheme (RTE) to mitigate the malicious behavior of the nodes within IoT networks. The nodes are grouped into a set of clusters each having a cluster head while cluster members are categorized by evaluating their associated residual energy. Nodes with residual energy lower than the threshold (which is determined by the base station) are suspended until they recover and regain their activity. The computations are handled by the CH which is elected by an algorithm according to its energy and coverage degree in order to optimize the energy consumption in the network. For validation and performance evaluation, the proposed RTE scheme was compared to three of the recent schemes in its category. The obtained results have revealed that the proposed RTE scheme outperforms all of them in terms of detection rate, trust evaluation time, and energy efficiency.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.