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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Allison, B.: Trends in BCI research: progress today, backlash tomorrow? The ACM Magazine for Students 18, 18–22 (2011)
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)
Brown, L.: Computer Security: Principles and Practice. William Stallings (2008)
Grubin, C., Madsen, L.: Lie detection and the polygraph: A historical review. The Journal of Forensic Psychiatry & Psychology 16, 357–369 (2005)
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)
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)
Leeb, R., Brunner, C., Muller-Putz, G., Schlogl, A., Pfurtscheller, G.: BCI Competition 2008 - Graz data set B, http://www.bbci.de/competition/iv/
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)
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)
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)
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)
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)
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)
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)
Palaniappan, R.: Two-stage biometric authentication method using thought activity brain waves. International Journal of Neural Systems 18 (2008)
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)
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)
Rathgeb, C., Uhl, A.: A survey on biometric cryptosystems and cancelable biometrics. EURASIP Journal on Information Security (2011)
Sanei, S., Chambers, J.: EEG signal processing. Wiley-Interscience (2007)
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)
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)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights 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)