Extended Faulty Nodes and Event Identification for WSNs Using IDM and SMM

Abstract: Wireless sensor networks (WSN) have gained great popularity, mainly because they provide a low cost alternative to solving a great variety of real-world problem. Wireless Sensor Networks (WSN) are characterized by the dense deployment of sensor nodes that continuously observe physical phenomenon. In-network aggregation is an essential primitive for performing queries on sensor network data. Security in-network aggregation for wireless sensor networks (WSNs) is a necessary and challenging problem. The existing techniques involves identification of malicious activities when one neighbouring node is compromised. The proposed system introduce the integration of system monitoring modules and intrusion detection modules when multiple neighbouring faulty nodes occur in the network. And also propose an extended Kalman filter (EKF) based local detection mechanism to detect false injected data. Specifically, by collecting the information from its neighbours and by using EKF to predict their future states (actual in-network aggregated values).Each node aims at setting up a normal range of the neighbours‟ future transmitted aggregated values. This is challenging task because of potential high packet loss rate, time delay, harsh environment, and sensing uncertainty. Using aggregation function (average), obtain a theoretical threshold. By comparing this threshold value with the measured value, conclude the whether the event is malicious or not.

Keywords: Wireless sensor networks, IDS(Intrusion Detection System),EKF(Extended Kalman filter), In-Network Aggregation.