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Biometrics and data mining: Comparison of data mining-based keystroke dynamics methods for identity verification. (English) Zbl 1077.68894

Coello Coello, Carlos A. (ed.) et al., MICAI 2002: Advances in artificial intelligence. 2nd Mexican international conference, Mérida, Yucatán, Mexico, April 22–26, 2002. Proceedings. Berlin: Springer (ISBN 3-540-43475-5). Lect. Notes Comput. Sci. 2313, 460-469 (2002).
Summary: 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 Naïve Bayesian Classifier, Memory Based Learning, and statistics-based Keystroke Dynamics.
For the entire collection see [Zbl 0992.00042].

MSC:

68T99 Artificial intelligence
92C30 Physiology (general)
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