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