Intrusion Detection Approach Based on Clustering and Statistical Model for Wireless Sensor Networks
Yinghua Zhou, Hui Shen · 2015
In recent years, Intrusion detection has been the focus of security research for Wireless Sensor Networks (WSN).Some approaches or mechanisms have been designed for WSN.But none of them has been widely applied.In this paper, a scheme based on sensor node clustering and statistical model for WSN is presented.First, the sensor nodes are divided into several clusters by using k-means algorithm, and then a kind of anomaly detection algorithm based on statistical model is applied to different clusters for anomaly detection.It is shown through experiments that the scheme can decrease the false alarm rate and increase the detection rate in comparison with existing intrusion detection approaches.