Abstract
This paper studies ways to detect good users for biometric recognition based on keystroke dynamics. Keystroke dynamics is an active research field for the biometric scientific community. Despite the great efforts made during the last decades, the performance of keystroke dynamics recognition systems is far from the performance achieved by traditional hard biometrics. This is very pronounced for some users, who generate many recognition errors even with the most sophisticate recognition algorithms. On the other hand, previous works have demonstrated that some other users behave particularly well even with the simplest recognition algorithms. Our purpose here is to study ways to distinguish such classes of users using only the genuine enrollment data. The experiments comprise a public database and two popular recognition algorithms. The results show the effectiveness of the Kullback-Leibler divergence as a quality measure to categorize users in comparison with other four statistical measures.
Chapter PDF
Similar content being viewed by others
References
Peacock, A., Ke, X., Wilkerson, M.: Typing patterns: A key to user identication. IEEE Security and Privacy 2(5), 40–47 (2004)
Banerjee, S.P., Woodard, D.L.: Biometric authentication and identification using keystroke dynamics: a survey. Journal of Pattern Recognition Research 7, 116–139 (2012)
Bailey, K.O., Okolica, J.S., Peterson, G.L.: User identification and authentication using multimodal behavioral biometrics. Computers and Security 43, 77–89 (2014)
Gunetti, D., Picardi, C.: Keystroke analysis of free text. ACM Transactions on Information and System Security 8(3), 312–347 (2005)
Sim, T., Zhang, S., Janakiraman, R., Kumar, S.: Continuous verification using multimodal biometrics. IEEE Transactions on Pattern Analysis and Machine Intelligent 29(4), 687–700 (2007)
Hocquet, S., Ramel, J.Y., Cardot, H.: User classication for keystroke dynamics authentication. In: International Conference on Biometrics, Seoul, Korea, pp. 531–539 (2007)
Alonso-Fernandez, F., Fierrez, J., Ortega-Garcia, J.: Quality measures in biometric systems. IEEE Security and Privacy 10(9), 52–62 (2012)
Chen, Y., Dass, S.C., Jain, A.K.: Fingerprint quality indices for predicting authentication performance. In: International Conference on Audio and Video-Based Biometric Person Authentication, Hilton Rye Town, NY, USA, pp. 160–170 (2005)
Youmaran, R., Adler, A.: Measuring biometric sample quality in terms of biometric information. In: Biometrics Symposium, Baltimore, USA (2006)
Killourhy, K., Maxion, R.: Why did my detector do That?! predicting keystroke-dynamics error rates. In: Jha, S., Sommer, R., Kreibich, C. (eds.) RAID 2010. LNCS, vol. 6307, pp. 256–276. Springer, Heidelberg (2010)
Fierrez-Aguilar, J., Ortega-Garcia, J., Gonzalez-Rodriguez, J., Bigun, J.: Discriminative multimodal biometric authentication based on quality measures. Pattern Recognition 38(5), 777–779 (2005)
Hong, L., Wan, Y., Jain, A.K.: Fingerprint image enhancement: Algorithm and performance evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence 20, 777–789 (1998)
Fiérrez-Aguilar, J., Chen, Y., Ortega-Garcia, J., K.Jain, A.: Incorporating image quality in multi-algorithm fingerprint verification. In: Zhang, D., Jain, A.K. (eds.) ICB 2005. LNCS, vol. 3832, pp. 213–220. Springer, Heidelberg (2005)
Kumar, A., Zhang, D.: Improving biometric authentication performance from the user quality. IEEE Transactions on Instrumentation and Measurement 59(3), 730–735 (2010)
Prabhakar, S., Pankanti, S., Jain, A.K.: Biometric recognition: Security and privacy concerns. IEEE Security Privacy Magacine 1(2), 33–42 (2003)
Doddington, G., Liggett, W., Martin, A., Przybocki, M., Reynolds, D.: Sheep, goats, lambs and wolves: a statistical analysis of speaker performance in the nist 1998 speaker recognition evaluation. In: International Confenrence on Spoken Language Processing, Sydney, Austrailia (1998)
Yager, N., Dunstone, T.: The biometric menagerie. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(2), 220–230 (2010)
Zhong, Y., Deng, Y., Jain, A.K.: Keystroke dynamics for user authentication. In: IEEE Computer Society Workshop on Biometrics, Providence, USA (2012)
Killourhy, K.S., Maxion, R.A.: Comparing anomaly detectors for keystroke dynamics. In: International Conference on Dependable Systems and Networks, Estoril, Portugal, vol. 32, pp. 125–134 (2009)
Kang, P., Park, S., Hwang, S., Lee, H., Cho, S.: Improvement of keystroke data quality through artificial rhythms and cues. Computers and Security 27, 3–11 (2008)
Cho, S., Hwang, S.: Artificial rhythms and cues for keystroke dynamics based authentication. In: Zhang, D., Jain, A.K. (eds.) ICB 2005. LNCS, vol. 3832, pp. 626–632. Springer, Heidelberg (2005)
Houmani, N., Garcia-Salicetti, S., Dorizzi, B.: A novel personal entropy measure confronted with online signature verification systems performance. In: IEEE Conference on Biometrics: Theory, Applications and Systems, Washington, USA, pp. 1–6 (2008)
Deng, Y., Zhong, Y.: Keystroke dynamics user authentication based on gaussian mixture model and deep belief nets. ISRN Signal Processing 2013, 1–7 (2013)
Killourhy, K.S., Maxion, R.A.: Image quality measures and their performance. IEEE Transactions on Communications 43(12), 2959–2965 (1995)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Morales, A., Fierrez, J., Ortega-Garcia, J. (2015). Towards Predicting Good Users for Biometric Recognition Based on Keystroke Dynamics. In: Agapito, L., Bronstein, M., Rother, C. (eds) Computer Vision - ECCV 2014 Workshops. ECCV 2014. Lecture Notes in Computer Science(), vol 8926. Springer, Cham. https://doi.org/10.1007/978-3-319-16181-5_54
Download citation
DOI: https://doi.org/10.1007/978-3-319-16181-5_54
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16180-8
Online ISBN: 978-3-319-16181-5
eBook Packages: Computer ScienceComputer Science (R0)