Probabilistic anomaly detection for wireless sensor networks

Authors:
Alfonso Farruggia;Giuseppe Lo Re;Marco Ortolani
Affiliations:
DICGIM, University of Palermo, Palermo;DICGIM, University of Palermo, Palermo;DICGIM, University of Palermo, Palermo
Venue:
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
Year:
2011

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Abstract

Wireless Sensor Networks (WSN) are increasingly gaining popularity as a tool for environmental monitoring, however ensuring the reliability of their operation is not trivial, and faulty sensors are not uncommon; moreover, the deployment environment may influence the correct functioning of a sensor node, which might thus be mistakenly classified as damaged. In this paper we propose a probabilistic algorithm to detect a faulty node considering its sensed data, and the surrounding environmental conditions. The algorithm was tested with a real dataset acquired in a work environment, characterized by the presence of actuators that also affect the actual trend of the monitored physical quantities.