NDLI: A PCA-based distributed approach for intrusion detection in wireless sensor networks

Content Provider	IEEE Xplore Digital Library
Author	Livani, M.A. Abadi, M.
Copyright Year	2011
Description	Author affiliation: Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran (Livani, M.A.; Abadi, M.)
Abstract	Wireless sensor networks (WSNs) are applied to various applications, ranging from military to civilian fields. Due to the critical nature of such applications, security issues are of significant importance. WSNs are vulnerable to different types of attacks since they are often deployed in hostile and unprotected environments. In this paper, we present a novel distributed intrusion detection approach, called PCADID, for detecting routing attacks in WSNs. In the approach, we partition a WSN into groups of sensor nodes. In each group, some nodes are selected as monitor nodes, which cooperate with each other to compose a global normal profile. Every monitor node establishes a subprofile of its own normal network traffic using principal component analysis (PCA) and sends it to other monitor nodes. Every monitor node composes the global normal profile based upon all received subprofiles and uses it to detect anomalies in its own network traffic. As the normal network behavior changes over time, the global normal profile is updated. We demonstrate that PCADID achieves a high detection rate with a low false alarm rate, while minimizes the communication overhead and energy consumption in the network.
Starting Page	55
Ending Page	60
File Size	417330
Page Count	6
File Format	PDF
ISBN	9781424491537
e-ISBN	9781424491544
DOI	10.1109/CNDS.2011.5764585
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-02-23
Publisher Place	Iran
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Routing attack Wireless sensor network Wireless sensor networks Intrusion detection Support vector machine classification Feature extraction Routing Monitoring Distributed intrusion detection Principal component analysis
Content Type	Text
Resource Type	Article

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