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Issue No. 04 - July-Aug. (2013 vol. 15)
ISSN: 1520-9202
pp: 24-28
Sun-Yuan Kung , Princeton University
Amed E. Kamal , Iowa State University
Stephen Gilbert , Iowa State University
Yixiao Ding , Iowa State University
Chris Chu , Iowa State University
Norene Kelly , Iowa State University
Pei-Yuan Wu , Princeton University
J. Morris Chang , Iowa State University
Kuan-Hsing Ho , Iowa State University
Chi-Chen Fang , Iowa State University
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.
Biometrics (access control), Keystrokes, Authentication, Training, Fingerprint recognition, information technology, security, continuous authentication, keystroke dynamics
Sun-Yuan Kung, Amed E. Kamal, Stephen Gilbert, Yixiao Ding, Chris Chu, Norene Kelly, Pei-Yuan Wu, J. Morris Chang, Kuan-Hsing Ho, Chi-Chen Fang, "Capturing Cognitive Fingerprints from Keystroke Dynamics", IT Professional, vol. 15, no. , pp. 24-28, July-Aug. 2013, doi:10.1109/MITP.2013.52
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