An Isolation Principle Based Distributed Anomaly Detection Method in Wireless Sensor Networks

Anomaly detection plays an important role in ensuring the data quality in wireless sensor networks (WSNs). The main objective of the paper is to design a light-weight and distributed algorithm to detect the data collected from WSNs effectively. This is achieved by proposing a distributed anomaly detection algorithm based on ensemble isolation principle. The new method offers distinctive advantages over the existing methods. Firstly, it does not require any distance or density measurement, which reduces computational burdens significantly. Secondly, considering the spatial correlation characteristic of node deployment in WSNs, local sub-detector is built in each sensor node, which is broadcasted simultaneously to neighbor sensor nodes. A global detector model is then constructed by using the local detector model and the neighbor detector model, which possesses a distributed nature and decreases communication burden. The experiment results on the labeled dataset confirm the effectiveness of the proposed method.