An Intrusion Detection Model for Wireless Sensor Networks With an Improved V-Detector Algorithm

Due to the advantage of negative selection algorithm (NSA) in classification domain, this paper proposes an intrusion detection model named as wireless sensor networks (WSN-NSA) based on an improved V-detector algorithm for WSN. To overcome the problem of resource constraints of storage space, computing capacity and energy in WSN, the main strategy of the WSN-NSA is to establish a three level detection mechanism by taking the advantage of the cooperation of the base station, detection nodes, and ordinary nodes considering their different capabilities, and to modify the V-detector algorithm by modifying the detector generation rule and optimizing the detectors, and to use the principal component analysis to reduce the detection features. Two kinds of detectors sets which are memory detector set and mature detector set are used to detect the intrusion. The simulation results show that the proposed model outperforms the intrusion detection systems using the V-detector in the reduction of data storage space and computation, the increased detection rate, and the quick response to the secondary attack.