Comparison between Mixed Binary classification and Voting Technique for Active User Authentication using Mouse Dynamics

Alnour Ahmed Khalifa*, Mutasim Adil Hassan, Tarig Ahmed Khalid, Hassan Hamdoun

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    4 Citations (Scopus)

    Abstract

    The rapid proliferation of computing processing power has facilitated a rise in the adoption of computers in various aspects of human lives. From education to shopping and other everyday activities to critical applications in finance, banking and, recently, degree awarding online education. Several approaches for user authentication based on Behavioral Biometrics (BB) were suggested in order to identify unique signature/footprint for improved matching accuracy for genuine users and flagging for abnormal behaviors from intruders. In this paper we present a comparison between two classification algorithms for identifying users' behavior using mouse dynamics. The algorithms are based on support vector machines (SVM) classifier allowing for direct comparison between different authentication-based metrics. The voting technique shows low False Acceptance Rate(FAR) and noticeably small learning time; making it more suitable for incorporation within different authentication applications.

    Original languageEnglish
    Title of host publication2015 International Conference on Computing, Control, Networking, Electronics and Embedded Systems Engineering (ICCNEEE)
    EditorsRA Saeed, RA Mokhtar
    PublisherIEEE Press
    Pages281-286
    Number of pages6
    ISBN (Electronic)978-1-4673-7869-7
    ISBN (Print)978-1-4673-7870-3
    DOIs
    Publication statusPublished - 2015
    EventIEEEE- The International Conference on Computing, Control, Networking, Electronics and Embedded Systems Engineering (ICCNEEE 2015) - Sudan, Khartoum, Sudan
    Duration: 7 Sep 20159 Sep 2015

    Conference

    ConferenceIEEEE- The International Conference on Computing, Control, Networking, Electronics and Embedded Systems Engineering (ICCNEEE 2015)
    CountrySudan
    CityKhartoum
    Period7/09/159/09/15

    Keywords

    • active authentication
    • mouse dynamics
    • pattern recognition
    • machine learning
    • support vector machines
    • Biometrics (access control)
    • Artificial neural networks

    ASJC Scopus subject areas

    • Computer Science(all)
    • Engineering(all)

    Cite this

    Khalifa, A. A., Hassan, M. A., Khalid, T. A., & Hamdoun, H. (2015). Comparison between Mixed Binary classification and Voting Technique for Active User Authentication using Mouse Dynamics. In RA. Saeed, & RA. Mokhtar (Eds.), 2015 International Conference on Computing, Control, Networking, Electronics and Embedded Systems Engineering (ICCNEEE) (pp. 281-286). IEEE Press. https://doi.org/10.1109/ICCNEEE.2015.7381378