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Proceedings Paper

Distance-based classification of keystroke dynamics
Author(s): Ngoc Tran Nguyen
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Paper Abstract

This paper uses the keystroke dynamics in user authentication. The relationship between the distance metrics and the data template, for the first time, was analyzed and new distance based algorithm for keystroke dynamics classification was proposed. The results of the experiments on the CMU keystroke dynamics benchmark dataset1 were evaluated with an equal error rate of 0.0614. The classifiers using the proposed distance metric outperform existing top performing keystroke dynamics classifiers which use traditional distance metrics.

Paper Details

Date Published: 11 July 2016
PDF: 6 pages
Proc. SPIE 10011, First International Workshop on Pattern Recognition, 100111E (11 July 2016); doi: 10.1117/12.2242022
Show Author Affiliations
Ngoc Tran Nguyen, Le Quy Don Technical Univ. (Viet Nam)


Published in SPIE Proceedings Vol. 10011:
First International Workshop on Pattern Recognition
Xudong Jiang; Guojian Chen; Genci Capi; Chiharu Ishll, Editor(s)

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