A Novel Feature Subset Selection Algorithm Using Artificial Bee Colony in Keystroke Dynamics

被引：0
|
作者：
Akila, M. [1 ]
Kumar, V. Suresh [2 ]
Anusheela, N. [3 ]
Sugumar, K. [1 ]
机构：
[1] CSI Coll Engn, Dept Comp Sci & Engn, Ketti, Tamil Nadu, India
[2] Vivekanandha Coll Technol, Dept Comp Sci & Engn, Tiruchengode, Tamil Nadu, India
[3] CSI Coll Engn, Dept Math, Ketti, Tamilnadu, India
来源：
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SOFT COMPUTING FOR PROBLEM SOLVING (SOCPROS 2011), VOL 2 | 2012年 / 131卷
关键词：
Feature extraction; Feature subset selection; Artificial Bee Colony algorithm (ABC); Neural network; ROC;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Keystroke dynamics is a biometric technique to identify a user based on the analysis of his/her typing rhythm. The steps of keystroke dynamics include feature extraction, feature subset selection and classifier. In the experiment mean, median and standard deviation of feature values such as latency, duration and digraph are measured in feature extraction. A meta-heuristic based on artificial bee colony algorithm is proposed for feature selection. Neural network is used for classification. The performance of artificial bee colony algorithm is analyzed with regard to feature reduction rate. The obtained result shows comparable quality with faster convergence.
引用
收藏
页码：813 / +
页数：3
相关论文
共 50 条
  • [21] A multi-objective Artificial Bee Colony algorithm for cost-sensitive subset selection
    Hancer, Emrah
    NEURAL COMPUTING & APPLICATIONS, 2022, 34 (20): : 17523 - 17537
  • [22] Parameters Optimization of Classifier and Feature Selection Based On Improved Artificial Bee Colony Algorithm
    Wang, Haiquan
    Yu, Hongnian
    Zhang, Qian
    Cang, Shuang
    Liao, Wudai
    Zhu, Fanbing
    2016 INTERNATIONAL CONFERENCE ON ADVANCED MECHATRONIC SYSTEMS (ICAMECHS), 2016, : 242 - 247
  • [23] A Stereo Remote Sensing Feature Selection Method Based on Artificial Bee Colony Algorithm
    Yan, Yiming
    Liu, Pigang
    Zhang, Ye
    Su, Nan
    Tian, Shu
    Gao, Fengjiao
    Shen, Yi
    SATELLITE DATA COMPRESSION, COMMUNICATIONS, AND PROCESSING X, 2014, 9124
  • [24] Multilevel Image Thresholding Selection Using the Artificial Bee Colony Algorithm
    Horng, Ming-Huwi
    Jiang, Ting-Wei
    ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, AICI 2010, PT II, 2010, 6320 : 318 - 325
  • [25] Utilizing Artificial Bee Colony Algorithm as Feature Selection Method in Arabic Text Classification
    Hijazi, Musab Mustafa
    Zeki, Akram
    Ismail, Amelia
    INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY, 2023, 20 (3A) : 536 - 547
  • [26] Feature Selection with Artificial Bee Colony Algorithm on Z-Alizadeh Sani Dataset
    Kilic, Umit
    Kaya Keles, Mumine
    2018 INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS CONFERENCE (ASYU), 2018, : 60 - 62
  • [27] Stock Selection by using an improved quick Artificial Bee Colony Algorithm
    Suthiwong, Dit
    Sodanil, Maleerat
    Quirchmayr, Gerald
    Unger, Herwig
    2017 21ST INTERNATIONAL COMPUTER SCIENCE AND ENGINEERING CONFERENCE (ICSEC 2017), 2017, : 40 - 44
  • [28] Web Service Selection Using Modified Artificial Bee Colony Algorithm
    Chandra, Manik
    Niyogi, Rajdeep
    IEEE ACCESS, 2019, 7 : 88673 - 88684
  • [29] Classifier ensemble design using artificial bee colony based feature selection
    Palanisamy, Shunmugapriya
    Kanmani, S.
    International Journal of Computer Science Issues, 2012, 9 (3 3-2): : 522 - 529
  • [30] A novel binary artificial bee colony algorithm
    Santana, Clodomir J., Jr.
    Macedo, Mariana
    Siqueira, Hugo
    Gokhale, Anu
    Bastos-Filho, Carmelo J. A.
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 98 : 180 - 196
12345