“3D Face”: Biometric Template Protection for 3D Face Recognition

  • E. J. C. Kelkboom
  • B. Gökberk
  • T. A. M. Kevenaar
  • A. H. M. Akkermans
  • M. van der Veen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)


In this paper we apply template protection to an authentication system based on 3D face data in order to protect the privacy of its users. We use the template protection system based on the helper data system (HDS). The experimental results performed on the FRGC v2.0 database demonstrate that the performance of the protected system is of the same order as the performance of the unprotected system. The protected system has a performance of a FAR ≈ 0.19% and a FRR ≈ 16% with a security level of 35 bits.


Template protection privacy protection helper data system (HDS) 3D face recognition 


  1. 1.
  2. 2.
    Juels, A., Wattenberg, M.: A fuzzy commitment scheme. In: 6th ACM Conference on Computer and Communications Security, pp. 28–36. ACM Press, New York (1999)CrossRefGoogle Scholar
  3. 3.
    Juels, A., Sudan, M.: A fuzzy vault scheme. In: ISIT 2002. Proc. of the 2002 International Symposium on Information Theory, Lausanne (2002)Google Scholar
  4. 4.
    Ratha, N.K., Connell, J.H., Bolle, R.M.: Enhancing security and privacy in biometrics-based authentication systems. IBM Systems Journal 40, 614–634 (2001)CrossRefGoogle Scholar
  5. 5.
    Dodis, Y., Reyzin, L., Smith, A.: Fuzzy extractors: How to generate strong secret keys from biometrics and other noisy data. In: Cachin, C., Camenisch, J.L. (eds.) EUROCRYPT 2004. LNCS, vol. 3027, pp. 532–540. Springer, Heidelberg (2004)Google Scholar
  6. 6.
    Verbitskiy, E., Tuyls, P., Denteneer, D., Linnartz, J.P.: Reliable biometric authentication with privacy protection. In: Proc. of the 24th Symp. on Inf. Theory in the Benelux, Veldhoven, The Netherlands, pp. 125–132 (2003)Google Scholar
  7. 7.
    Linnartz, J.-P., Tuyls, P.: New shielding functions to enhance privacy and prevent misuse of biometric templates. In: Kittler, J., Nixon, M.S. (eds.) AVBPA 2003. LNCS, vol. 2688, Springer, Heidelberg (2003)CrossRefGoogle Scholar
  8. 8.
    Kevenaar, T.A.M., Schrijen, G.-J., Akkermans, A.H.M., van der Veen, M., Zou, F.: Face recognition with renewable and privacy preserving binary templates. In: 4th IEEE workshop on AutoID, Buffalo, New York, USA, pp. 21–26. IEEE Computer Society Press, Los Alamitos (2005)Google Scholar
  9. 9.
    Tuyls, P., Akkermans, A.H.M., Kevenaar, T.A.M., Schrijnen, G.J., Bazen, A.M., Veldhuis, R.N.J.: Pratical biometric authentication with template protection. In: Kanade, T., Jain, A., Ratha, N.K. (eds.) AVBPA 2005. LNCS, vol. 3546, Springer, Heidelberg (2005)Google Scholar
  10. 10.
    Gökberk, B., Irfanoglu, M.O., Akarun, L.: 3D shape-based face representation and feature extraction for face recognition. Image and Vision Computing 24, 857–869 (2006)CrossRefGoogle Scholar
  11. 11.
    Purser, M.: Introduction to Error-Correcting Codes. Artech House, Boston (1995)zbMATHGoogle Scholar
  12. 12.
    Phillips, P.J., Flynn, P.J., Scruggs, T., Bowyer, K.W., Chang, J., Hoffman, K., Marques, J., Min, J., Worek, W.: Overview of the face recognition grand challenge. In: IEEE CVPR, vol. 2, pp. 454–461. IEEE Computer Society Press, Los Alamitos (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • E. J. C. Kelkboom
    • 1
  • B. Gökberk
    • 1
  • T. A. M. Kevenaar
    • 1
  • A. H. M. Akkermans
    • 1
  • M. van der Veen
    • 1
  1. 1.Philips Research, High-Tech Campus 34, 5656AE, Eindhoven 

Personalised recommendations