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dc.contributor.authorIvannikova, Elena
dc.contributor.authorDavid, Gil
dc.contributor.authorHämäläinen, Timo
dc.date.accessioned2017-12-13T12:31:53Z
dc.date.available2017-12-13T12:31:53Z
dc.date.issued2017
dc.identifier.citationIvannikova, E., David, G., & Hämäläinen, T. (2017). Anomaly detection approach to keystroke dynamics based user authentication. In <em>ISCC 2017 : Proceedings of the 2017 IEEE Symposium on Computers and Communications</em> (pp. 885-889). IEEE. <a href="https://doi.org/10.1109/ISCC.2017.8024638">doi:10.1109/ISCC.2017.8024638</a>
dc.identifier.otherTUTKAID_75404
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/56305
dc.description.abstractKeystroke dynamics is one of the authentication mechanisms which uses natural typing pattern of a user for identification. In this work, we introduced Dependence Clustering based approach to user authentication using keystroke dynamics. In addition, we applied a k-NN-based approach that demonstrated strong results. Most of the existing approaches use only genuine users data for training and validation. We designed a cross validation procedure with artificially generated impostor samples that improves the learning process yet allows fair comparison to previous works. We evaluated the methods using the CMU keystroke dynamics benchmark dataset. Both proposed approaches outperformed the previous state-of-the-art results for the CMU dataset for unsupervised learning.
dc.format.extent1385
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartofISCC 2017 : Proceedings of the 2017 IEEE Symposium on Computers and Communications, ISBN 978-1-5386-1629-1
dc.subject.othertietoturva
dc.subject.otherpääsynvalvonta
dc.subject.othertodentaminen
dc.subject.otherdata security
dc.subject.otheraccess control
dc.subject.otherauthentication
dc.titleAnomaly detection approach to keystroke dynamics based user authentication
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-201712134659
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineTietotekniikka
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.date.updated2017-12-13T10:15:10Z
dc.relation.isbn978-1-5386-1629-1
dc.type.coarconference paper
dc.description.reviewstatuspeerReviewed
dc.format.pagerange885-889
dc.relation.issn1530-1346
dc.type.versionacceptedVersion
dc.rights.copyright© 2017 IEEE. This is a final draft of an article whose final and definitive version has been published by IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.rights.accesslevelopenAccessfi
dc.relation.doi10.1109/ISCC.2017.8024638


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