Keystroke Biometric System Using Wavelets

  • Woojin Chang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3832)

Abstract

We developed the keystroke biometric system (KBS) using the statistical features of the discrete wavelet transformed keystroke pattern in the frequency domain in addition to those of the original keystroke pattern in the time domain. Only 20 keystroke patterns of user’s password typing, where the length of password is no more than 10, are used for building a KBS. The features in the time domain and those in the frequency domain are separately scored by the rules that we developed, and arbitrary given keystroke patterns are classified on the basis of total scores. The results show that our KBS is competitive in comparison with others due to its cheap computational cost, cheap usability cost, and the practically acceptable classification accuracy.

Keywords

Keystroke Dynamics Keystroke Biometric System Key- stroke Authentication Discrete Wavelet Transform 

References

  1. 1.
    Vidakovic, B.: Statistical Modeling by Wavelets. Wiley, Chichester (1999)MATHCrossRefGoogle Scholar
  2. 2.
    Peacock, A., Ke, X., Wilkerson, M.: Typing Patterns: A Key to User Identification. IEEE Securiy & Privacy 2, 40–47 (2004)CrossRefGoogle Scholar
  3. 3.
    Yu, E., Cho, S.: Keystroke dynamics identy verification–its problems and practical solutions. Computers & Security 23, 428–440 (2004)CrossRefGoogle Scholar
  4. 4.
    Sheng, Y., Phoha, V.V., Rovnyak, S.M.: A Parallel Decision Tree-Based Method for User Authentication Based on Keystroke Patterns. IEEE Trans. Sytems, Man and Cybernetics, Part B. 35, 826–833 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Woojin Chang
    • 1
  1. 1.Department of Industrial EngineeringSeoul National UniversitySeoulKorea

Personalised recommendations