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Feature Selection and Representation of Evolutionary Algorithm on Keystroke Dynamics

Purvashi Baynath, Sunjiv Soyjaudah, Maleika Heenaye-Mamode Khan

University of Mauritius, Reduit, Mauritius

* Corresponding Author: Purvashi Baynath, email

Intelligent Automation & Soft Computing 2019, 25(4), 651-661. https://doi.org/10.31209/2018.100000060

Abstract

The goal of this paper is (i) adopt fusion of features (ii) determine the best method of feature selection technique among ant Colony optimisation, artificial bee colony optimisation and genetic algorithm. The experimental results reported that ant colony Optimisation is a promising techniques as feature selection on Keystroke Dynamics as it outperforms in terms of recognition rate for our inbuilt database where the distance between the keys has been considered for the password derivation with recognition rate 97.85%. Finally the results have shown that a small improvement is obtained by fused features, which suggest that an effective fusion is necessary.

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Cite This Article

APA Style
Baynath, P., Soyjaudah, S., Khan, M.H. (2019). Feature selection and representation of evolutionary algorithm on keystroke dynamics. Intelligent Automation & Soft Computing, 25(4), 651-661. https://doi.org/10.31209/2018.100000060
Vancouver Style
Baynath P, Soyjaudah S, Khan MH. Feature selection and representation of evolutionary algorithm on keystroke dynamics. Intell Automat Soft Comput . 2019;25(4):651-661 https://doi.org/10.31209/2018.100000060
IEEE Style
P. Baynath, S. Soyjaudah, and M.H. Khan "Feature Selection and Representation of Evolutionary Algorithm on Keystroke Dynamics," Intell. Automat. Soft Comput. , vol. 25, no. 4, pp. 651-661. 2019. https://doi.org/10.31209/2018.100000060



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