11 July 2016 Distance-based classification of keystroke dynamics
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Proceedings Volume 10011, First International Workshop on Pattern Recognition; 100111E (2016) https://doi.org/10.1117/12.2242022
Event: First International Workshop on Pattern Recognition, 2016, Tokyo, Japan
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.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ngoc Tran Nguyen, "Distance-based classification of keystroke dynamics", Proc. SPIE 10011, First International Workshop on Pattern Recognition, 100111E (11 July 2016); doi: 10.1117/12.2242022; https://doi.org/10.1117/12.2242022
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