A User Authentication Technic Using a~Web Interaction Monitoring System

  • Hugo Gamboa
  • Ana Fred
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2652)


User authentication based on biometrics has explored both physiological and behavioral characteristics. We present a system, called Web Interaction Display and Monitoring (WIDAM), that captures an user interaction on the web via a pointing device. This forms the basis of a new authentication system that uses behavioral information extracted from these interaction signals. The user interaction logs produced by WIDAM are presented to a sequential classifier, that applies statistical pattern recognition techniques to ascertain the identity of an individual – authentication system. The overall performance of the combined acquisition / authentication systems is measured by the global equal error rate, estimated from a test set. Preliminary results show that the new technique is a promising tool for user authentication, exhibiting comparable performances to other behavioural biometric techniques. Exploring standard human-computer interaction devices, and enabling remote access to behavioural information, this system constitutes an inexpensive and practical approach to user authentication through the world wide web.


User Interaction User Authentication Equal Error Rate Authentication System False Rejection Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Abernethy, R.B.: The New Weibull Handbook. Robert B. Abernethy (2000)Google Scholar
  2. 2.
    BenZeghiba, M.F., Bourlard, H., Mariethoz, J.: Speaker verification based on user-customized password. Technical Report IDIAP-RR 01-13, Institut Dalle Molle d’Intelligence Artificial Perceprive (2001)Google Scholar
  3. 3.
    Efron, B., Tibshirani, R.J.: An Introduction to the Bootstrap. Chapman & Hall, Boca Raton (1993)zbMATHGoogle Scholar
  4. 4.
    Gamboa, H., Ferreira, V.: WIDAM - Web Interaction Display and Monitoring. In: Proceedings of the 5th International Conference on Enterprise Information Systems, vol. 4, pp. 21–27 (2003)Google Scholar
  5. 5.
    Gamboa, H., Fred, A.: An Identity Authentication System Based On Human Computer Interaction Behaviour. In: Proceedings of the 3rd International Workshop on Pattern Recognition in Information Systems, pp. 46–55 (2003)Google Scholar
  6. 6.
    Gupta, J., McCabe, A.: A review of dynamic handwritten signature verification. Technical report, James Cook University, Australia (1997)Google Scholar
  7. 7.
    Hors, A.L., Hgaret, P.L., Wood, L.: Document object model level 2 core. Technical report, W3C (2000)Google Scholar
  8. 8.
    Jain, A.K., Duin, R.P.W., Mao, J.: Statistical pattern recognition: A review. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(1) (2000)Google Scholar
  9. 9.
    Matyas Jr., V., Riha, Z.: Biometric authentication systems. Technical report, ECOM-MONITOR (2000)Google Scholar
  10. 10.
    Mansfield, T., Roethenbaugh, G.: 1999 glossary of biometric terms. Technical report, Association for Biometrics (1999)Google Scholar
  11. 11.
    Pixley, T.: Document object model (dom) level 2 events specification. Technical report, W3C (2000)Google Scholar
  12. 12.
    Ruggles, T.: Comparison of biometric techniques. Technical report, California Welfare Fraud Prevention System (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Hugo Gamboa
    • 1
  • Ana Fred
    • 2
  1. 1.Escola Superior de Tecnologia de SetúbalSetúbalPortugal
  2. 2.Instituto de Telecomunicações Instituto Superior Técnico, ISTLisboaPortugal

Personalised recommendations