Advertisement

Biometric Authentication with Electroencephalograms: Evaluation of Its Suitability Using Visual Evoked Potentials

  • André Zúquete
  • Bruno Quintela
  • João Paulo Silva Cunha
Part of the Communications in Computer and Information Science book series (CCIS, volume 127)

Abstract

This paper studies the suitability of brain activity, namely electroencephalogram signals, as raw material for conducting biometric authentication of individuals. Brain responses were extracted in particular scenarios, namely with visual stimulation leading to biological brain responses known as visual evoked potentials. In our study, we evaluated a novel method, using only 8 occipital electrodes and the energy of differential EEG signals, to extract information about the subjects for further use as their biometric features. To classify the features obtained from each individual we used a one-class classifier per subject. These classifiers are trained only with target class features, which is the correct procedure to apply in biometric authentication scenarios. Two types of one-class classifiers were tested, K-Nearest Neighbor and Support Vector Data Description. Two other classifier architectures were also studied, both resulting from the combination of the two previously mentioned classifiers. After testing these classifiers with the features extracted from 70 subjects, the results showed that brain responses to visual stimuli are suitable for an accurate biometric authentication.

Keywords

Area Under Curve Visual Evoke Potential Authentication System Biometric Authentication Common Spatial Pattern 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Başar, E.: Relation between EEG and Brain Evoked Potentials. In: EEG-Brain Dynamics. Elsevier, North-Holland biomedical Press, Amsterdam (1980)Google Scholar
  2. 2.
    Başar, E., Rosen, B., Başar-Eroglu, C., Greitschus, F.: The associations between 40 Hz-EEG the Middle Latency Response of the Auditory and Evoked Potential. The Int. J. of Neuroscience 33(1-2), 103–117 (1987)CrossRefGoogle Scholar
  3. 3.
    Basar, E., Basar-Eroglu, C., Demiralp, T., Schrmann, M.: Time and Frequency Analysis of the Brain’s Distributed Gamma-Band System. IEEE Eng. in Medicine and Biology 14, 400–410 (1995)CrossRefGoogle Scholar
  4. 4.
    Davies, D., Bouldin, D.: A Cluster Separation Measure. IEEE Trans. on Pattern Analysis and Mach. Intelligence 1(2), 224–227 (1979)CrossRefGoogle Scholar
  5. 5.
    Elman, J.L.: Finding structure in time. Cognitive Science 14(2), 179–211 (1990)CrossRefGoogle Scholar
  6. 6.
    Galambos, R.: A comparison of certain gamma band (40-Hz) brain rhythms in cat and man. In: Induced Rhythms in the Brain, pp. 201–216. Birkhuser, Boston (1992)Google Scholar
  7. 7.
    Gruber, T., Mller, M.M., Keil, A.: Modulation of Induced Gamma Band Responses in a Perceptual Learning Task in the Human EEG. J. of Cognitive Neuroscience 14(5), 732–744 (2002)CrossRefGoogle Scholar
  8. 8.
    Jain, A., Hong, L., Pankanti, S.: Biometric Identification. Communications of the ACM 43(2), 90–98 (2000)CrossRefGoogle Scholar
  9. 9.
    Kasuba, T.: Simplified Fuzzy ARTMAP, pp. 18–25. AI Expert, USA (1993)Google Scholar
  10. 10.
    Keil, A., Mller, M.M., Ray, W.J., Gruber, T., Elbert, T.: Human Gamma Band Activity and Perception of a Gestalt. The J. of Neuroscience 19(16), 7152–7161 (1999)Google Scholar
  11. 11.
    Kohonen, T.: Self-organization and associative memory, 3rd edn. Springer, New York (1989)Google Scholar
  12. 12.
    Marcel, S., del Millán, J.R.: Person Authentication Using Brainwaves (EEG) and Maximum A Posteriori Model Adaptation. IEEE Trans. on Pattern Analysis and Mach. Intelligence 29(4), 743–748 (2007)CrossRefGoogle Scholar
  13. 13.
    Palaniappan, R.: Method of identifying individuals using VEP signals and neural network. IEE Proc. - Science Measurement and Technology 151(1), 16–20 (2004)CrossRefGoogle Scholar
  14. 14.
    Palaniappan, R.: Two-stage biometric authentication method using thought activity brain waves. Int. J. of Neural Systems 18(1) (2008)Google Scholar
  15. 15.
    Palaniappan, R., Mandic, D.P.: Energy of Brain Potentials Evoked During Visual Stimulus: A New Biometric? In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds.) ICANN 2005. LNCS, vol. 3697, pp. 735–740. Springer, Heidelberg (2005)Google Scholar
  16. 16.
    Palaniappan, R., Mandic, D.P.: EEG Based Biometric Framework for Automatic Identity Verification. J. of VLSI Signal Processing 49, 243–250 (2007)CrossRefGoogle Scholar
  17. 17.
    Poulos, M., Rangousi, M., Kafetzopoulos, E.: Person identification via the EEG using computational geometry algorithms. In: Proc. of the 9th European Signal Processing (EUSIPCO 1998), Rhodes, Greece, pp. 2125–2128 (1998)Google Scholar
  18. 18.
    Poulos, M., Rangoussi, M., Chrissikopoulos, V., Evangelou, A.: Person Identification Based on Parametric Processing of the EEG. In: Proc. of the 6th IEEE Int. Conf. on Electronics, Circuits and Systems (ICECS), pp. 283–286 (1999)Google Scholar
  19. 19.
    Ravi, K.V.R., Palaniappan, R.: Leave-one-out Authentication of Persons Using 40 Hz EEG Oscillations. In: Proc. of the Int. Conf. on ”Computer as a tool” (EUROCON 2005), Belgrade, Serbia & Montenegro (November 2005)Google Scholar
  20. 20.
    Ravi, K.V.R., Palaniappan, R.: Recognising Individuals Using Their Brain Patterns. In: Proc. of the 3th Int. Conf. on Information Tech. and Applications (ICITA 2005). IEEE Computer Society, Los Alamitos (2005)Google Scholar
  21. 21.
    Ravi, K.V.R., Palaniappan, R.: Neural network classification of late gamma band electroencephalogram features. Soft Computing 10, 163–169 (2006)CrossRefGoogle Scholar
  22. 22.
    Regan, D., Neima, D.: Visual fatigue and visual evoked potentials in multiple sclerosis, glaucoma, ocular hypertension and Parkinson’s disease. Journal of Neurology, Neurosurgery, and Psychiatry 47(7) (July 1984)Google Scholar
  23. 23.
    Rhodes, L.E., Obitz, F.W., Creel, D.: Effect of alcohol and task on hemispheric asymmetry of visually evoked potentials in man. Electroencephalography Clinical Neurophysiology 38(6), 561–568 (1975)CrossRefGoogle Scholar
  24. 24.
    Riera, A., Soria-Frisch, A., Caparrini, M., Grau, C., Ruffini, G.: Unobtrusive Biometric System Based on Electroencephalogram Analysis. In: EURASIP J. on Advances in Signal Processing 2008 (2008)Google Scholar
  25. 25.
    Sivakumar, R., Ravindran, G.: Identification of Intermediate Latencies in Transient Visual Evoked Potentials. Academic Open Internet J. 17 (2006)Google Scholar
  26. 26.
    Snodgrass, J.G., Vanderwart, M.: A Standardized Set of 260 Pictures: Norms for Name Agreement, Image Agreement, Familarity and Visual Complexity. J. of Experimental Psychology: Human Learning and Memory 6(2), 174–215 (1980)CrossRefGoogle Scholar
  27. 27.
    Sun, S.: Multitask learning for eeg-based biometrics. In: 19th Int. Conf. on Pattern Recognition (ICPR 2008), Tampa, Florida, USA (December 2008)Google Scholar
  28. 28.
    Tallon-Baudry, C., Bertrand, O., Peronnet, F., Pernier, J.: Induced γ-Band Activity during the Delay of a Visual Short-Term Memory Task in Humans. The J. of Neuroscience 18(11), 4244–4254 (1998)Google Scholar
  29. 29.
    Tax, D.M.J.: One-class classification; Concept-learning in the absence of counter-examples. Ph.D. thesis, Delft University of Technology, Delft, Netherlands (June 2001)Google Scholar
  30. 30.
    Lutzenberger, W., Pulvermllera, F., Elbertb, T., Birbaumer, N.: Visual stimulation alters local 40-Hz responses in humans: an EEG-study. Neuroscience Letters 183(1-2), 39–42 (1995)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • André Zúquete
    • 1
  • Bruno Quintela
    • 2
  • João Paulo Silva Cunha
    • 1
  1. 1.IEETA / University of AveiroAveiroPortugal
  2. 2.University of AveiroAveiroPortugal

Personalised recommendations