Abstract
Smart grids require communication networks to convey sensing and control data for improving the efficiency of energy generation, transmission, and delivery. As a result, smart girds become vulnerable to various types of cyber-attacks. Trust models were recognized as one of the important methods of defending a large communication network against malicious cyber-attacks. In this paper, a fuzzy logic trust model is proposed to detect untrusted nodes in smart grid networks, and compared with an existing model to show its advantages. Using this proposed model, both the routing efficiency and the detection rate for all types of considered malicious behaviors can be improved. In comparison with the existing lightweight and dependable trust system model, the proposed model improves the packet dropping rate by up to 90% when the percentage of malicious nodes is less than 25%, as verified by simulations.
Highlights
A S a result of immense widespread of Internet, a new concept that connects all objects together, known as Internet of Things (IoT), has emerged
Smart grid communication architecture consists of three layers [2], [3], as shown in Fig. 1: first layer is a Home Area Network (HAN) which consists of all devices within the home or building that is connected with smart meters; second layer is a Neighborhood Area Network (NAN) that is composed of many HANs and a base station; and third layer is a Wide Area Network (WAN) where base stations forward the concentrated metering data to Metering Data Management System (MDMS)
If the percentage of malicious nodes is less than 25%, the dropping rate is very small;
Summary
Abstract—Smart grids require communication networks to convey sensing and control data for improving the efficiency of energy generation, transmission and delivery. Smart girds become vulnerable to various types of cyber-attacks. Trust models were recognized as one of the important methods of defending a large communication network against malicious cyber-attacks. A fuzzy logic trust model is proposed to detect untrusted nodes in smart grid networks, and compared with an existing model to show its advantages. Using this proposed model, both the routing efficiency and the detection rate for all types of considered malicious behaviors can be improved. In comparison with the existing Lightweight and Dependable Trust System (LDTS) model, the proposed model improves the packet dropping rate by up to 90% when the percentage of malicious nodes is less than 25%, as verified by simulations
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