A Novel Algorithm for Improving Malicious Node Detection Effect in Wireless Sensor Networks

Abstract

As an important medium of information transmitting, Wireless Sensor Networks (WSN) is at risk of a series of malicious nodes. In view of the inefficiency of the existing malicious node detection methods in Wireless Sensor Networks, this paper proposed a malicious node detection model based on reputation with enhanced low energy adaptive clustering hierarchy (Enhanced LEACH) routing protocol (MNDREL). MNDREL is a novel algorithm, which is aimed at identifying malicious nodes in the wireless sensor network (WSN) more efficiently. Cluster-head nodes are first selected based on the enhanced LEACH routing protocol. Other nodes in WSN then form different clusters by selecting corresponding cluster-head nodes and determine the packets delivery paths. Each node then adds its node number and reputation evaluation value to the packet before sending it to the sink node. A list of suspicious nodes is then formed by comparing the node numbers, obtained through parsing with the packets by the sink node, with the source node numbers. To determine the malicious nodes in the network, the ratio of the suspect value to the trusted value of each node is further calculated and compared with a predefined threshold. The algorithm proposed in this paper, with other two state-of-the-art methods, which are the fuzzy logic based multi-attribute trust model (FMATM) and the high-reliability trust evaluation model (HRTM), are performed and analysed in the same scenario. According to simulation experiments, the MNDREL model is more efficient in detecting malicious nodes in WSN with lower false alarm rate.