Theoretical Framework for Constructing Matching Algorithms in Biometric Authentication Systems

  • Manabu Inuma
  • Akira Otsuka
  • Hideki Imai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5558)

Abstract

In this paper, we propose a theoretical framework to construct matching algorithms for any biometric authentication systems. Conventional matching algorithms are not necessarily secure against strong intentional impersonation attacks such as wolf attacks. The wolf attack is an attempt to impersonate a genuine user by presenting a “wolf” to a biometric authentication system without the knowledge of a genuine user’s biometric sample. A “wolf” is a sample which can be accepted as a match with multiple templates. The wolf attack probability (WAP) is the maximum success probability of the wolf attack, which was proposed by Une, Otsuka, Imai as a measure for evaluating security of biometric authentication systems [UOI1], [UOI2]. We present a principle for construction of secure matching algorithms against the wolf attack for any biometric authentication systems. The ideal matching algorithm determines a threshold for each input value depending on the entropy of the probability distribution of the (Hamming) distances. Then we show that if the information about the probability distribution for each input value is perfectly given, then our matching algorithm is secure against the wolf attack. Our generalized matching algorithm gives a theoretical framework to construct secure matching algorithms. How lower WAP is achievable depends on how accurately the entropy is estimated. Then there is a trade-off between the efficiency and the achievable WAP. Almost every conventional matching algorithm employs a fixed threshold and hence it can be regarded as an efficient but insecure instance of our theoretical framework. Daugman’s algorithm proposed in [Da2] can also be regarded as a non-optimal instance of our framework.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [AYL1]
    Adler, A., Youmaran, R., Loyka, S.: Towards a measure of biometric feature information. In: Pattern Analysis and Applications. Springer, London (Online first), doi:10.1007/s10044-008-0120-3Google Scholar
  2. [Da1]
    Daugman, J.: High Confidence Visual Recognition of Persons by a Test of Statstical Independence. IEEE Trans. on Pattern Anal. Mach. Intell. 15(11) (November 1993)Google Scholar
  3. [Da2]
    Daugman, J.: Probing the uniqueness and randomness of IrisCodes: Results from 200 billion iris pair comparisons. Proceedings of the IEEE 94(11), 1927–1935 (2006)Google Scholar
  4. [ISO1]
    International Organization for Standardization (ISO), International Electronical Commission (ICE): ISO/IEC CD 19792: Imformation technology - Security techniques - Security evaluations of biometrics (2006)Google Scholar
  5. [Ka1]
    Kevenaar, T.: Protection of Biometric Information. In: Tuyls, P., Skoric, B., Kevenaar, T. (eds.) Security with Noisy Data: On Private Biometrics, Secure Key Storage and Anti-Counterfeiting, ch. 7, pp. 113–125. Springer, London (2007)Google Scholar
  6. [MMYH1]
    Matsumoto, T., Matsumoto, H., Yamada, K., Hoshino, S.: Impact of Artificial ‘Gummy’ Fingers on Fingerprinting Systems. In: Opt. Sec. and Count. Det. Tech. IV, Proc. of SPIE, vol. 4677, pp. 275–289 (2002)Google Scholar
  7. [RCB1]
    Ratha, N.K., Connell, J.H., Bolle, R.M.: Enhancing security and privacy in biometrics-based authentication systems. IBM Syst. J. 40, 614–634 (2001)Google Scholar
  8. [UOI1]
    Une, M., Otsuka, A., Imai, H.: Wolf Attack Probability: A New Security Measure in Biometric Authentication Systems. In: Lee, S.-W., Li, S.Z. (eds.) ICB 2007. LNCS, vol. 4642, pp. 396–406. Springer, Heidelberg (2007)Google Scholar
  9. [UOI2]
    Une, M., Otsuka, A., Imai, H.: Wolf Attack Probability: A Theoretical Security Measure in Biometrics-Based Authentication Systems. IEICE, Transactions on Information and Systems 2008 E91-D (5), 1380–1389 (2008)Google Scholar
  10. [Wa1]
    Wayman, J.S.: The cotton ball problem. In: Biometrics Conference, Washington, DC, USA, September 20-22 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Manabu Inuma
    • 1
    • 2
  • Akira Otsuka
    • 1
    • 2
  • Hideki Imai
    • 1
    • 2
  1. 1.Research Center for Information Security (RCIS)National Institute of Advanced Industrial Science and Technology (AIST)TokyoJapan
  2. 2.Department of Electrical, Electronic, and Communication Engineering Faculty of Science and EngineeringChuo UniversityTokyoJapan

Personalised recommendations