Dynamic identity verification via keystroke characteristics
International Journal of Man-Machine Studies
User identification via keystroke characteristics of typed names using neural networks
International Journal of Man-Machine Studies
Verification of computer users using keystroke dynamics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An evolutionary keystroke authentication based on ellipsoidal hypothesis space
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Expert Systems with Applications: An International Journal
Account-Sharing Detection Through Keystroke Dynamics Analysis
International Journal of Electronic Commerce
GREYC keystroke: a benchmark for keystroke dynamics biometric systems
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Keystroke dynamics with low constraints SVM based passphrase enrollment
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Review Article: Biometric personal authentication using keystroke dynamics: A review
Applied Soft Computing
WISI'06 Proceedings of the 2006 international conference on Intelligence and Security Informatics
The effectiveness of artificial rhythms and cues in keystroke dynamics based user authentication
WISI'06 Proceedings of the 2006 international conference on Intelligence and Security Informatics
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Biometrics based user authentication involves collecting user’s patterns and then using them to determine if a new pattern is similar enough. The quality of the user’s patterns is as important as the quality of the classifier. But, the issue has been ignored in the literature since the popular biometrics are mostly trait based such as finger prints and iris so that its pattern quality depends on the quality of the input device involved. However, the quality of the user’s patterns of behavior based biometric such as keystroke dynamics can be improved artificially by increasing the peculiarity of the typing style. In this paper, we propose several ways to improve the quality. But, first we define the quality of patterns in terms of two factors: uniqueness and consistency. Finally, the results of a preliminary experiment are presented that support the utility of the proposed methods.