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

Zhi-Guo Ding; Da-Jun Du; Min-Rui Fei

doi:10.1007/s11633-014-0847-9

Volume 12 Issue 4

August 2015

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Zhi-Guo Ding, Da-Jun Du and Min-Rui Fei. An Isolation Principle Based Distributed Anomaly Detection Method in Wireless Sensor Networks. International Journal of Automation and Computing, vol. 12, no. 4, pp. 402-412, 2015. https://doi.org/10.1007/s11633-014-0847-9

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

doi: 10.1007/s11633-014-0847-9

Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China;
College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua 321004, China

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This work was supported by the National High Technology Research and Development Program of China (No. 2011AA040103-7), the National Key Scientific Instrument and Equipment Development Project (No. 2012YQ15008703), the Zhejiang Provincial Natural Science Foundation of China (No. LY13F020015), National Science Foundation of China (No. 61104089), Science and Technology Commission of Shanghai Municipality (No. 11JC1404000), and Shanghai Rising-Star Program (No. 13QA1401600).

Received Date: 2013-10-09
Rev Recd Date: 2014-03-28
Publish Date: 2015-08-01

Abstract

Abstract

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.
- Distributed anomaly detection,
- isolation principle,
- light-weight method,
- ensemble learning,
- wireless sensor networks (WSNs)

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