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Capturing Cognitive Fingerprints from Keystroke Dynamics
IT Professional
  • J. Morris Chang, Iowa State University
  • Chi-Chen Fang, Iowa State University
  • Kuan-Hsing Ho, Iowa State University
  • Norene Kelly, Iowa State University
  • Pei-Yuan Wu, Princeton University
  • Yixiao Ding, Iowa State University
  • Chris Chu
  • Stephen B Gilbert, Iowa State University
  • Amed E. Kamal, Iowa State University
  • Sun-Yuan Kung, Princeton University
Document Type
Article
Publication Version
Submitted Manuscript
Publication Date
6-1-2013
DOI
10.1109/MITP.2013.52
Abstract
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.
Comments

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." IT Professional 15, no. 4 (2013): 24-28. DOI:10.1109/MITP.2013.52. Posted with permission.

Rights
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Copyright Owner
IEEE
Language
en
File Format
application/pdf
Citation Information
J. Morris Chang, Chi-Chen Fang, Kuan-Hsing Ho, Norene Kelly, et al.. "Capturing Cognitive Fingerprints from Keystroke Dynamics" IT Professional Vol. 15 Iss. 4 (2013) p. 24 - 28
Available at: http://works.bepress.com/morris-chang/1/