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Robust and Secure Biometrics: Some Application Examples

  • T. Kevenaar
  • G. J. Schrijen
  • A. Akkermans
  • M. Damstra
  • P. Tuyls
  • M. van der Veen

Abstract

In the past years there has been much theoretical interest in secure extraction of robust strings from noisy measurements. In particular this technique allows extracting robust cryptographic keys from noisy biometric data. This paper starts with an overview of the ideas behind robust and secure string extraction in terms of information reconciliation, privacy amplification and helper data. The main part of the paper gives three application examples explaining how these techniques are used to enhance the convenience and security of devices (e.g. tokens) while preserving also the privacy of the user because neither biometric information nor secret cryptographic keys need to be stored on applications. We discuss a server access token, a 3-way check for a biometric ePassport and a password vault.

Keywords

Server Access Biometric System Compression Function International Civil Aviation Organization Biometric Measurement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [BrSa93]
    Brassard, G, Salvail, L.: Secret-key reconciliation by Public Discussion, Advances in Cryptology, EUROCRYPT’93, Springer Verlag, LNCS 765, 1994, p.410–423.Google Scholar
  2. [GaMa94]
    Gander, M. J., Maurer, U. M.: On the secret-key rate of binary random variables. Proc.1994 IEEE International Symposium on Information Theory, p.351, 1994.Google Scholar
  3. [KayO5]
    Roger L. Kay, “Protecting Mobility”, IDC White paper, 2005 http://www.synaptics.com/support/Protecting_Mobility.pdf
  4. [KSV+05]
    Kevenaar, T. A. M, Schrijen, G. J., van der Veen, M., Akkermans, A. H. M. and Zuo, F.: Face Recognition with Renewable and Privacy Preserving Templates. Proc. 4th IEEE Workshop on Automatic Identification Advanced Technologies (AutolD 2005), Springer Verlag, LNCS 3546, 2005, p.21–25.Google Scholar
  5. [LiTuO3]
    Linnartz, J. P and Tuyls P.: New shielding functions to enhance privacy and prevent misuse of biometric templates, Proc. 3rd Conf. Audio and Video Based Person Authentication (AVBPA 2003), Springer Verlag, LNCS 2688, 2003, p.238–250.Google Scholar
  6. [MaWo99]
    Maurer, U. M., Wolf, S.: Unconditional Secure Key Agreement and the Intrinsic Conditional Information, IEEE Trans. on Information Theory, Vol. 45, no. 2, 1999, p.499–514.MATHCrossRefMathSciNetGoogle Scholar
  7. [TuGoO4]
    Tuyls P. and Goseling J.: Capacity and Examples of Template Protecting Biometric Authentication Systems, Proc. Biometric Authentication Workshop (BioAW, Prague 2004), Springer Verlag, LNCS 3087, 2004, p.158–170.Google Scholar
  8. [ShouOS]
    V. Shoup, “A Computational Introduction to Number Theory and Algebra”, Cambridge University Press 2005.Google Scholar

Copyright information

© Friedr. Vieweg & Sohn Verlag | GWV-Fachverlage GmbH, Wiesbaden 2006

Authors and Affiliations

  • T. Kevenaar
  • G. J. Schrijen
  • A. Akkermans
    • 1
  • M. Damstra
    • 1
  • P. Tuyls
    • 1
  • M. van der Veen
    • 1
  1. 1.Philips Research EuropeEindhovenThe Netherlands

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