Energy Efficient Approach for Intrusion Detection System for WSN by applying Optimal Clustering and Genetic Algorithm

Abstract

Ubiquitous computing is modifying the presence of human being in the current epoch. Smart home is solitary of the emerging instances for omnipresent computing solicitations. Wireless Sensor Network can hypothetically be responsible for information about environmental and confidential activities and their status. This information can be expedient for assortment of tenacities like monitoring home sanctuary, exploratory status of nodes, and replacing nodes that are deficient or dead. The sensor network needs to be protected from intrusions, anomalies and incongruities. Concluded ages, numerous intrusion detection systems are anticipated for thwarting wireless sensor networks from intrusions. This research work is taking conventional probabilistic clustering protocol concepts, also considering heterogeneity and behaviour based detection procedure in wireless sensor network as an effective way to increase the detection accuracy, network lifetime and stability. Various issues in Wireless Sensor Networks are formulated as multidimensional optimization problems, and impend through self-organizing concept and intrusion detection architecture. In this paper, we have proposed an optimized cluster based approach for intrusion detection system using genetic algorithm, to make an optimized agent selection process and adaptive intrusion detection which depends upon prevailing network conditions and resource status. Here, simulation results have shown that with this network designing the network efficiency and stability period have increased extensively.