Feature Selection and Representation of Evolutionary Algorithm on Keystroke Dynamics

被引：3
|
作者：
Baynath, Purvashi [1 ]
Soyjaudah, Sunjiv [1 ]
Khan, Maleika Heenaye-Mamode [1 ]
机构：
[1] Univ Mauritius, Reduit, Mauritius
来源：
INTELLIGENT AUTOMATION AND SOFT COMPUTING | 2019年 / 25卷 / 04期
关键词：
Artificial Bee Colony Optimization; Ant colony Optimization; Artificial Neural Network; Biometrics; Genetic Algorithm; Keystroke Dynamics; VERIFICATION;
D O I：
10.31209/2018.100000060
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：651 / 661
页数：11
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