Biometrics and Data Mining: Comparison of Data Mining-Based Keystroke Dynamics Methods for Identity Verification

Authors:
Francisco J. Gutiérrez;Margarita M. Lerma-Rascón;Luis R. Salgado-Garza;Francisco J. Cantu
Affiliations:
-;-;-;-
Venue:
MICAI '02 Proceedings of the Second Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Year:
2002

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Abstract

Biometrics is the field that differentiates among various people based on their unique biological and physiological patterns such as retina, finger prints, DNA and keyboard typing patterns to name a few. Keystroke Dynamics is a physiological biometric that measures the unique typing rhythm and cadence of a computer keyboard user. This paper presents a Data Mining-based Keystroke Dynamics application for identity verification, and it reports the results of experiments comparing different approaches to Keystroke Dynamics. The methods compared were Decision Trees, a Na茂ve Bayesian Classifier, Memory Based Learning, and statistics-based Keystroke Dynamics.