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

摘要

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 Naive Bayesian Classifier, Memory Based Learning, and statistics-based Keystroke Dynamics.