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Bahrepour, M. and Zhang, Yang and Meratnia, N. and Havinga, P.J.M. (2009) Use of Event Detection Approaches for Outlier Detection in Wireless Sensor Networks. In: Proceedings of Symposium on Theoretical and Practical Aspects of Large-scale Wireless Sensor Networks, The 5th International Conference on Intelligent Sensors, Sensor Networks and Information Processing 2009 (ISSNIP 2009), 7-10 Dec 2009, Melbourne, Australia. pp. 439-444. IEEE Press. ISBN 978-1-4244-3518-0
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Official URL: http://dx.doi.org/10.1109/ISSNIP.2009.5416749
Outliers or anomalies are generally considered to be those observations that are considerably diverged from normal pattern of data. Due to their special characteristics, e.g. constrained available resources, frequent physical failure, and often harsh deployment area, wireless sensor networks (WSNs) are more likely to generate outliers compared to their other wireless counterparts. Potential sources of deviated data in a series of measurements are errors, events, and/or malicious attacks on the network. Current studies tend to handle events and errors separately and propose different techniques for event detection as for outlier detection. By bringing the concept of outlier and event close together and assuming that events are some sorts of outliers, in this paper, we investigate applicability of pattern matching-based event detection techniques for outlier detection. Through extensive experiments, we evaluate performance of various event detection techniques to detect outliers and compare them with a recent outlier detection study.
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