Distance-based classification of keystroke dynamics

Ngoc Tran Nguyen

doi:10.1117/12.2242022

11 July 2016 Distance-based classification of keystroke dynamics

Ngoc Tran Nguyen

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.

Citation Download Citation

Ngoc Tran Nguyen "Distance-based classification of keystroke dynamics", Proc. SPIE 10011, First International Workshop on Pattern Recognition, 100111E (11 July 2016); https://doi.org/10.1117/12.2242022

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