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dc.contributor.convenorWanlei Zhou and Ahmad-Reza Sadeghien_US
dc.contributor.authorWu, Xin-Wenen_US
dc.contributor.authorZi, Lifangen_US
dc.contributor.authorYearwood, Johnen_US
dc.contributor.editorYang Xiang, Pierangela Samarati, Jiankun Hu, Wanlie Zhou, Ahmad-Reza Sadeghien_US
dc.date.accessioned2017-05-03T15:50:36Z
dc.date.available2017-05-03T15:50:36Z
dc.date.issued2010en_US
dc.date.modified2012-09-02T23:20:18Z
dc.identifier.refurihttp://anss.org.au/nss2010/en_US
dc.identifier.doi10.1109/NSS.2010.70en_US
dc.identifier.urihttp://hdl.handle.net/10072/37326
dc.description.abstractDistributed Denial of Service (DDoS) attacks pose an increasing threat to the current internet. The detection of such attacks plays an important role in maintaining the security of networks. In this paper, we propose a novel adaptive clustering method combined with feature ranking for DDoS attacks detection. First, based on the analysis of network traffic, preliminary variables are selected. Second, the Modified Global K-means algorithm (MGKM) is used as the basic incremental clustering algorithm to identify the cluster structure of the target data. Third, the linear correlation coefficient is used for feature ranking. Lastly, the feature ranking result is used to inform and recalculate the clusters. This adaptive process can make worthwhile adjustments to the working feature vector according to different patterns of DDoS attacks, and can improve the quality of the clusters and the effectiveness of the clustering algorithm. The experimental results demonstrate that our method is effective and adaptive in detecting the separate phases of DDoS attacks.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.format.extent423176 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_US
dc.publisherIEEEen_US
dc.publisher.placeUSAen_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofconferencenameNSS 2010 -Fourth International Conference on Network and System Securityen_US
dc.relation.ispartofconferencetitleProceedings of 2010 Fourth International Conference on Network and System Security - NSS 2010en_US
dc.relation.ispartofdatefrom2010-09-01en_US
dc.relation.ispartofdateto2010-09-03en_US
dc.relation.ispartoflocationMelbourneen_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchData Encryptionen_US
dc.subject.fieldofresearchInformation Systems not elsewhere classifieden_US
dc.subject.fieldofresearchcode080402en_US
dc.subject.fieldofresearchcode080699en_US
dc.titleAdaptive Clustering with Feature Ranking for DDoS Attacks Detectionen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.facultyGriffith Sciences, Griffith School of Engineeringen_US
gro.rights.copyrightCopyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_US
gro.date.issued2010
gro.hasfulltextFull Text


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    Contains papers delivered by Griffith authors at national and international conferences.

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