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Detecting selective forwarding attacks in wireless sensor networks using support vector machines
conference contribution
posted on 2007-01-01, 00:00 authored by S Kaplantzis, Alistair ShiltonAlistair Shilton, N Mani, Y A ŞekerciǧluWireless Sensor Networks (WSNs) are a new technology foreseen to be used increasingly in the near future due to their data acquisition and data processing abilities. Security for WSNs is an area that needs to be considered in order to protect the functionality of these networks, the data they convey and the location of their members. The security models and protocols used in wired and other networks are not suited to WSNs because of their severe resource constraints, especially concerning energy . In this article, we propose a centralized intrusion detection scheme based on Support Vector Machines (SVMs) and sliding windows. We find that our system can detect black hole attacks and selective forwarding attacks with high accuracy without depleting the nodes of their energy.
History
Event
Australian Research Council. Conference (3rd : 2007 : Melbourne, Vic.)Series
Australian Research Council ConferencePagination
335 - 340Publisher
Institute of Electrical and Electronics EngineersLocation
Melbourne, Vic.Place of publication
Piscataway, N.J.Publisher DOI
Start date
2007-12-03End date
2007-12-06ISBN-13
9781424415021ISBN-10
1424415020Language
engPublication classification
E1.1 Full written paper - refereedEditor/Contributor(s)
M Palaniswami, S Marusic, Y LawTitle of proceedings
ISSNIP 2007 : Proceedings of the 2007 International Conference on Intelligent Sensors, Sensor Networks and Information ProcessingUsage metrics
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