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Efficiency Issues and Improving Implementation of Keystroke Biometric Systems
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Author(s): Ali Kartit (LTI Laboratory, ENSAJ, Chouaib Doukkali University, Morocco)and Farida Jaha (LTI Laboratory, ENSAJ, Chouaib Doukkali University, Morocco)
Copyright: 2020
Pages: 13
Source title:
Encyclopedia of Criminal Activities and the Deep Web
Source Author(s)/Editor(s): Mehdi Khosrow-Pour D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-9715-5.ch077
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Abstract
Keystroke dynamics is a heavy field for researches; a lot of solutions have been proposed in this domain using different implementations usually based on Euclidean distance for measuring similarity between features vectors. However, the Euclidean distance method has a higher error equal rate compared with other classification methods, which makes the method less effective. Therefore, in the article, the authors propose their version of keystroke dynamics implementation based on K-NN, F-NN, and Manhattan distance as classifiers to improve the authentication efficiency. The flight times and dwell time between keys are used in this study.
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