Abstract
Adaptive biometric recognition systems have been proposed to deal with natural changes of the clients’ biometric traits due to multiple factors, like aging. However, their adaptability to changes may be exploited by an attacker to compromise the stored templates, either to impersonate a specific client, or to deny access to him. In this paper we show how a carefully designed attack may gradually poison the template gallery of some users, and successfully mislead a simple PCA-based face verification system that performs self-update.
Chapter PDF
Similar content being viewed by others
Keywords
References
Barreno, M., Nelson, B., Sears, R., Joseph, A.D., Tygar, J.D.: Can machine learning be secure? In: Proc. Symp. on Information, Computer and Comm. Sec. (ASIACCS), pp. 16–25. ACM (2006)
Biggio, B., Akhtar, Z., Fumera, G., Marcialis, G.L., Roli, F.: Security evaluation of biometric authentication systems under real spoofing attacks. IET Biometrics 1(1), 11–24 (2012)
Jiang, X., Ser, W.: Online fingerprint template improvement. IEEE Trans. Pattern Analysis and Machine Intell. 24(8), 1121–1126 (2002)
Kloft, M., Laskov, P.: Online anomaly detection under adversarial impact. In: Proc. 13th Int’l Conf. on AI and Statistics (AISTATS), pp. 405–412 (2010)
Laskov, P., Lippmann, R.: Machine learning in adversarial environments. Machine Learning 81, 115–119 (2010)
Nelson, B., Joseph, A.D.: Bounding an attack’s complexity for a simple learning model. In: Proc. 1st Workshop on Tackling Computer Systems Problems with ML Techniques, SysML (2006)
Roli, F., Marcialis, G.L.: Semi-supervised PCA-Based Face Recognition Using Self-training. In: Yeung, D.-Y., Kwok, J.T., Fred, A., Roli, F., de Ridder, D. (eds.) SSPR 2006 and SPR 2006. LNCS, vol. 4109, pp. 560–568. Springer, Heidelberg (2006)
Ryu, C., Kim, H., Jain, A.K.: Template adaptation based fingerprint verification. In: Proc. 18th Int’l Conf. Pattern Rec., vol. 04, pp. 582–585. IEEE CS (2006)
Turk, M., Pentland, A.: Eigenfaces for recognition. J. Cogn. Neuroscience 3(1), 71–86 (1991)
Uludag, U., Ross, A., Jain, A.K.: Biometric template selection and update: a case study in fingerprints. Pattern Recognition 37(7), 1533–1542 (2004)
Yambor, W.S.: Analysis of PCA-based and Fisher discriminant-based image recognition algorithms. Technical Report, Colorado State University (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Biggio, B., Fumera, G., Roli, F., Didaci, L. (2012). Poisoning Adaptive Biometric Systems. In: Gimel’farb, G., et al. Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2012. Lecture Notes in Computer Science, vol 7626. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34166-3_46
Download citation
DOI: https://doi.org/10.1007/978-3-642-34166-3_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34165-6
Online ISBN: 978-3-642-34166-3
eBook Packages: Computer ScienceComputer Science (R0)