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
相关论文
共 50 条
  • [1] Feature Selection for Android Keystroke Dynamics
    El Zein, Dima
    Kalakech, Ali
    [J]. 2018 19TH INTERNATIONAL ARAB CONFERENCE ON INFORMATION TECHNOLOGY (ACIT), 2018, : 246 - 251
  • [2] A dexterous feature selection artificial immune system algorithm for keystroke dynamics
    Chandrasekar, V.
    Kumar, S. Suresh
    [J]. STOCHASTIC ANALYSIS AND APPLICATIONS, 2016, 34 (01) : 147 - 154
  • [3] User tuned feature selection in keystroke dynamics
    Amarnadh, Jyothi Bhaskarr
    Gamboa, Hugo
    Fred, Ana
    [J]. BIOSIGNALS 2008: PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON BIO-INSPIRED SYSTEMS AND SIGNAL PROCESSING, VOL II, 2008, : 546 - 550
  • [4] A Novel Feature Subset Selection Algorithm Using Artificial Bee Colony in Keystroke Dynamics
    Akila, M.
    Kumar, V. Suresh
    Anusheela, N.
    Sugumar, K.
    [J]. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SOFT COMPUTING FOR PROBLEM SOLVING (SOCPROS 2011), VOL 2, 2012, 131 : 813 - +
  • [5] Performance Comparison of Particle Swarm Optimization and Genetic Algorithm for Feature Subset Selection in Keystroke Dynamics
    Saini, Baljit Singh
    Kaur, Navdeep
    Bhatia, Kamaljit Singh
    [J]. PROCEEDINGS OF 2019 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND KNOWLEDGE ECONOMY (ICCIKE' 2019), 2019, : 685 - 690
  • [6] An approach to feature selection for keystroke dynamics systems based on PSO and feature weighting
    Azevedo, Gabriel L. F. B. G.
    Cavalcanti, George D. C.
    Carvalho Filho, E. C. B.
    [J]. 2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS, 2007, : 3577 - 3584
  • [7] An Efficient Feature Selection Technique for User Authentication using Keystroke Dynamics
    Shanmugapriya, D.
    Padmavathi, G.
    [J]. INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2011, 11 (10): : 191 - 195
  • [8] Hybrid solution for the feature selection in personal identification problems through keystroke dynamics
    Azevedo, Gabriel. L. F. B. G.
    Cavalcanti, George D. C.
    Carvalho Filho, E. C. B.
    [J]. 2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6, 2007, : 1947 - 1952
  • [9] Research on Feature Selection Based on Hybrid Evolutionary Algorithm
    Gao, Hui-Min
    Wang, Yun-He
    Bian, Chuang
    Li, Xiang-Tao
    [J]. Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2023, 51 (06): : 1619 - 1636
  • [10] Binary Representation of Polar Bear Algorithm for Feature Selection
    Mirkhan, Amer
    Celebi, Numan
    [J]. COMPUTER SYSTEMS SCIENCE AND ENGINEERING, 2022, 43 (02): : 767 - 783
12345