DocumentCode :
6730
Title :
Capturing Cognitive Fingerprints from Keystroke Dynamics
Author :
Chang, J.M. ; Chi-Chen Fang ; Kuan-Hsing Ho ; Kelly, Nicholas ; Pei-Yuan Wu ; Yixiao Ding ; Chu, Chris ; Gilbert, Stephen ; Kamal, Ahmed E. ; Sun-Yuan Kung
Author_Institution :
Iowa State Univ., Ames, IA, USA
Volume :
15
Issue :
4
fYear :
2013
fDate :
July-Aug. 2013
Firstpage :
24
Lastpage :
28
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.
Keywords :
fingerprint identification; message authentication; regression analysis; support vector machines; CTR; KRR; SVM; authentication system; cognitive fingerprint; cognitive typing rhythm; false-acceptance rate; false-rejection rate; kernel ridge regression; keystroke dynamics; Authentication; Biometrics (access control); Fingerprint recognition; Keystrokes; Training; continuous authentication; information technology; keystroke dynamics; security;
fLanguage :
English
Journal_Title :
IT Professional
Publisher :
ieee
ISSN :
1520-9202
Type :
jour
DOI :
10.1109/MITP.2013.52
Filename :
6545274
Link To Document :
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