File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: An efficient intruder detection algorithm against sinkhole attacks in wireless sensor networks

TitleAn efficient intruder detection algorithm against sinkhole attacks in wireless sensor networks
Authors
KeywordsIntruder detection
Wireless sensor network
Sinkhole attack
Intruder identification
Issue Date2007
Citation
Computer Communications, 2007, v. 30, n. 11-12, p. 2353-2364 How to Cite?
AbstractIn a wireless sensor network, multiple nodes would send sensor readings to a base station for further processing. It is known that such a many-to-one communication is highly vulnerable to a sinkhole attack, where an intruder attracts surrounding nodes with unfaithful routing information, and then performs selective forwarding or alters the data passing through it. A sinkhole attack forms a serious threat to sensor networks, particularly considering that the sensor nodes are often deployed in open areas and of weak computation and battery power. In this paper, we present a novel algorithm for detecting the intruder in a sinkhole attack. The algorithm first finds a list of suspected nodes through checking data consistency, and then effectively identifies the intruder in the list through analyzing the network flow information. The algorithm is also robust to deal with multiple malicious nodes that cooperatively hide the real intruder. We have evaluated the performance of the proposed algorithm through both numerical analysis and simulations, which confirmed the effectiveness and accuracy of the algorithm. Our results also suggest that its communication and computation overheads are reasonably low for wireless sensor networks. © 2007 Elsevier B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/281492
ISSN
2023 Impact Factor: 4.5
2023 SCImago Journal Rankings: 1.402
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorNgai, Edith C.H.-
dc.contributor.authorLiu, Jiangchuan-
dc.contributor.authorLyu, Michael R.-
dc.date.accessioned2020-03-13T10:38:00Z-
dc.date.available2020-03-13T10:38:00Z-
dc.date.issued2007-
dc.identifier.citationComputer Communications, 2007, v. 30, n. 11-12, p. 2353-2364-
dc.identifier.issn0140-3664-
dc.identifier.urihttp://hdl.handle.net/10722/281492-
dc.description.abstractIn a wireless sensor network, multiple nodes would send sensor readings to a base station for further processing. It is known that such a many-to-one communication is highly vulnerable to a sinkhole attack, where an intruder attracts surrounding nodes with unfaithful routing information, and then performs selective forwarding or alters the data passing through it. A sinkhole attack forms a serious threat to sensor networks, particularly considering that the sensor nodes are often deployed in open areas and of weak computation and battery power. In this paper, we present a novel algorithm for detecting the intruder in a sinkhole attack. The algorithm first finds a list of suspected nodes through checking data consistency, and then effectively identifies the intruder in the list through analyzing the network flow information. The algorithm is also robust to deal with multiple malicious nodes that cooperatively hide the real intruder. We have evaluated the performance of the proposed algorithm through both numerical analysis and simulations, which confirmed the effectiveness and accuracy of the algorithm. Our results also suggest that its communication and computation overheads are reasonably low for wireless sensor networks. © 2007 Elsevier B.V. All rights reserved.-
dc.languageeng-
dc.relation.ispartofComputer Communications-
dc.subjectIntruder detection-
dc.subjectWireless sensor network-
dc.subjectSinkhole attack-
dc.subjectIntruder identification-
dc.titleAn efficient intruder detection algorithm against sinkhole attacks in wireless sensor networks-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.comcom.2007.04.025-
dc.identifier.scopuseid_2-s2.0-34548031104-
dc.identifier.volume30-
dc.identifier.issue11-12-
dc.identifier.spage2353-
dc.identifier.epage2364-
dc.identifier.isiWOS:000249912500004-
dc.identifier.issnl0140-3664-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats