Detection of Hello Flood Attacks Using Fuzzy-Based Energy-Efficient Clustering Algorithm for Wireless Sensor Networks

Abstract

Clustering is one among the most important strategies to improve the lifetime of wireless sensor networks (WSNs). The frequent occurrence of clustering and the subsequent interchange of data overload the sensor nodes and result in wasting power. WSNs are susceptible to attacks because of their resource-constrained nature and large applications in critical military areas. The objective of the threats to the security of wireless sensor networks is to compromise the network by seizing information for misuse. Security features have become a major concern in these types of networks as it is important to protect sensitive data from unauthorized users. This paper aims to present an enriched clustering strategy to minimize the overhead caused by clustering, by formulating an effective cluster update schedule. It also focuses on the attacks that occur during an exchange of initialization messages with neighbors. Clustering of the network is carried out on the basis of the energy of sensor nodes. The nodes that are the heads of the cluster nodes are determined according to the characteristics of energy factors; hence, the role is frequently switched among the nodes of the cluster. To formulate the next cluster update schedule, a fuzzy inference system is employed, and this uses the energy factor of the node, the distance the node is placed from the sink, and the number of member nodes of the cluster. A mechanism is included during an exchange of initialization messages that detects any malicious node pretending to be a neighbor node. The proposed algorithm is evaluated using simulation, and it is found to produce an improved lifetime of 1700 time units. It is shown to conserve the energy of sensor nodes and protect them from unauthorized nodes posing as legitimate neighbors.