Capturing Cognitive Fingerprints from Keystroke Dynamics

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dc.contributor.author Chang, J.
dc.contributor.author Fang, Chi-Chen
dc.contributor.author Gilbert, Stephen
dc.contributor.author Ho, Kuan-Hsing
dc.contributor.author Kelly, Norene
dc.contributor.author Wu, Pei-Yuan
dc.contributor.author Ding, Yixiao
dc.contributor.author Chu, Chris
dc.contributor.author Chu, Chris Chong-Nuen
dc.contributor.author Kamal, Amed
dc.contributor.author Chang, Morris
dc.contributor.author Kung, Sun-Yuan
dc.contributor.department Virtual Reality Applications Center
dc.contributor.department Department of Electrical and Computer Engineering
dc.contributor.department Psychology
dc.contributor.department Department of Industrial and Manufacturing Systems Engineering
dc.contributor.department Human Computer Interaction
dc.date 2018-02-18T13:47:37.000
dc.date.accessioned 2020-06-30T04:47:51Z
dc.date.available 2020-06-30T04:47:51Z
dc.date.copyright Tue Jan 01 00:00:00 UTC 2013
dc.date.issued 2013-07-01
dc.description.abstract <p>Conventional authentication systems identify a user only at the entry point. Keystroke dynamics can continuously authenticate users by their typing rhythms without extra devices. This article presents a new feature called cognitive typing rhythm (CTR) to continuously verify the identities of computer users. Two machine techniques, SVM and KRR, have been developed for the system. The best results from experiments conducted with 1,977 users show a false-rejection rate of 0.7 percent and a false-acceptance rate of 5.5 percent. CTR therefore constitutes a cognitive fingerprint for continuous. Its effectiveness has been verified through a large-scale dataset. This article is part of a special issue on security.</p>
dc.description.comments <p>This is a manuscript of an article published as Chang, J. Morris, Chi-Chen Fang, Kuan-Hsing Ho, Norene Kelly, Pei-Yuan Wu, Yixiao Ding, Chris Chu, Stephen Gilbert, Amed E. Kamal, and Sun-Yuan Kung. "Capturing cognitive fingerprints from keystroke dynamics." <em>IT Professional</em> 15, no. 4 (2013): 24-28. DOI: <a href="http://dx.doi.org/10.1109/MITP.2013.52" target="_blank">10.1109/MITP.2013.52</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/imse_pubs/131/
dc.identifier.articleid 1134
dc.identifier.contextkey 10293853
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath imse_pubs/131
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/44421
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/imse_pubs/131/2013_Gilbert_CapturingCognitive.pdf|||Fri Jan 14 19:44:29 UTC 2022
dc.source.uri 10.1109/MITP.2013.52
dc.subject.disciplines Risk Analysis
dc.subject.disciplines Systems and Communications
dc.subject.disciplines Systems Engineering
dc.subject.keywords information technology
dc.subject.keywords security
dc.subject.keywords continuous authentication
dc.subject.keywords keystroke dynamics
dc.title Capturing Cognitive Fingerprints from Keystroke Dynamics
dc.type article
dc.type.genre article
dspace.entity.type Publication
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