Skip to main content

A Study on the Feasibility of Using EEG Signals for Authentication Purpose

  • Conference paper
Neural Information Processing (ICONIP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8227))

Included in the following conference series:

Abstract

Authentication is to verify if one is who he/she claims. It plays an important role in security systems. In this paper, we study the feasibility of using Electroencephalography (EEG) brain signals for authentication purpose. In a general sense, there are three types of authentications including password based, token based, and biometric based. Each of them has its own merit and drawback. Technology advancing makes it possible to easily obtain EEG signals. The evidences show that finding repeatable and stable brainwave patterns in EEG data is feasible. The prospect of using EEG signals for authentication is promising. An EEG based authentication system has the combined advantages of both password based and biometric based authentication systems, yet without their drawbacks. Therefore, it makes an EEG signal based authentication suitable for especially high security system. Through the analysis and processing of EEG signals of motor imagery from BCI Competition, our experiment results confirm the theories stated in this paper.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Allison, B.: Trends in BCI research: progress today, backlash tomorrow? The ACM Magazine for Students 18, 18–22 (2011)

    Article  Google Scholar 

  2. Ashby, C., Bhatia, A., Tenore, F., Vogelstein, J.: Low-cost electroencephalogram (EEG) based authentication. In: 2011 5th International IEEE/EMBS Conference on Neural Engineering (NER), pp. 442–445 (2011)

    Google Scholar 

  3. Brown, L.: Computer Security: Principles and Practice. William Stallings (2008)

    Google Scholar 

  4. Grubin, C., Madsen, L.: Lie detection and the polygraph: A historical review. The Journal of Forensic Psychiatry & Psychology 16, 357–369 (2005)

    Article  Google Scholar 

  5. He, C., Chen, H., Wang, Z.: Hashing the MAR Coefficients From EEG Data For Person Authentication. In: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2009, pp. 1445–1448 (2009)

    Google Scholar 

  6. Hu, J.: Biometric System based on EEG Signals by feature combination. In: 2010 International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), pp. 752–755 (2010)

    Google Scholar 

  7. Leeb, R., Brunner, C., Muller-Putz, G., Schlogl, A., Pfurtscheller, G.: BCI Competition 2008 - Graz data set B, http://www.bbci.de/competition/iv/

  8. Marcel, S., Millán, J.R.: Person authentication using brainwaves (EEG) and maximum a posteriori model adaptation. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(2007), 743–752 (2007)

    Article  Google Scholar 

  9. Ma, W., Campell, J., Tran, D., Kleeman, D.: Password Entropy and Password Quality. In: 2010 4th International Conference on Network and System Security (NSS), pp. 583–587 (2010)

    Google Scholar 

  10. Matyáš, V., Řiha, Z.: Security of biometric authentication systems. In: 2010 International Conference on Computer Information Systems and Industrial Management Applications (CISIM), pp. 18–28 (2010)

    Google Scholar 

  11. Nguyen, P., Tran, D., Le, T., Hoang, T.: Multi-sphere support vector data description for brain-computer interface. In: 2012 Fourth International Conference on Communications and Electronics (ICCE), pp. 318–321 (2012)

    Google Scholar 

  12. Nguyen, P., Tran, D., Le, T., Huang, X., Ma, W.: EEG-Based Person Verification Using Multi-Sphere SVDD and UBM. In: 17th Pacific-Asia Conference, pp. 289–300 (2013)

    Google Scholar 

  13. Nguyen, P., Tran, D., Huang, X., Sharma, D.: A Proposed Feature Extraction Method for EEG-based Person Identification. In: The International Conference on Artificial Intelligence (ICAI 2012), USA (2012)

    Google Scholar 

  14. Nguyen, P., Tran, D., Huang, X., Ma, W.: Motor Imagery EEG based Person Verification. In: Rojas, I., Joya, G., Cabestany, J. (eds.) IWANN 2013, Part II. LNCS, vol. 7903, pp. 430–438. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  15. Palaniappan, R.: Two-stage biometric authentication method using thought activity brain waves. International Journal of Neural Systems 18 (2008)

    Google Scholar 

  16. Poulos, M., Rangoussi, M., Alexandris, N.: Neural network based person identification using EEG features. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 1999, pp. 1117–1120 (1999)

    Google Scholar 

  17. Poulos, M., Rangoussi, M., Alexandris, N., Evangelou, A.: Person identification from the EEG using nonlinear signal classification. Methods of Information in Medicine 41(1), 64–75 (2002)

    Google Scholar 

  18. Rathgeb, C., Uhl, A.: A survey on biometric cryptosystems and cancelable biometrics. EURASIP Journal on Information Security (2011)

    Google Scholar 

  19. Sanei, S., Chambers, J.: EEG signal processing. Wiley-Interscience (2007)

    Google Scholar 

  20. Schaaff, K., Schult, S.: Towards emotion recognition from lectroencephalographic signals. In: 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009, pp. 1–6 (2009)

    Google Scholar 

  21. Yazdani, A., Roodaki, A., Rezatofighi, S.H., Misaghian, K., Setarehdan, S.K.: Fisher linear discriminant based person identification using visual evoked potentials. In: 9th International Conference on Signal Processing, ICSP 2008, pp. 1677–1680 (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Pham, T., Ma, W., Tran, D., Nguyen, P., Phung, D. (2013). A Study on the Feasibility of Using EEG Signals for Authentication Purpose. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42042-9_70

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-42042-9_70

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-42041-2

  • Online ISBN: 978-3-642-42042-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics