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An adaptive elliptical anomaly detection model for wireless sensor networks

journal contribution
posted on 2014-05-08, 00:00 authored by M Moshtaghi, C Leckie, S Karunasekera, Sutharshan RajasegararSutharshan Rajasegarar
Wireless Sensor Networks (WSNs) provide a low cost option for monitoring different environments such as farms, forests and water and electricity networks. However, the restricted energy resources of the network impede the collection of raw monitoring data from all the nodes to a single location for analysis. This has stimulated research into efficient anomaly detection techniques to extract information about unusual events such as malicious attacks or faulty sensors at each node. Many previous anomaly detection methods have relied on centralized processing of measurement data, which is highly communication intensive. In this paper, we present an efficient algorithm to detect anomalies in a decentralized manner. In particular, we propose a novel adaptive model for anomaly detection, as well as a robust method for modeling normal behavior. Our evaluation results on both real-life and simulated data sets demonstrate the accuracy of our approach compared to existing methods.

History

Journal

Computer networks

Volume

64

Pagination

195-207

Location

Amsterdam, The Netherlands

ISSN

1389-1286

Language

eng

Publication classification

C Journal article, C1.1 Refereed article in a scholarly journal

Copyright notice

2014, Elsevier

Publisher

Elsevier