Advertisement

Embedding Renewable Cryptographic Keys into Continuous Noisy Data

  • Ileana Buhan
  • Jeroen Doumen
  • Pieter Hartel
  • Qiang Tang
  • Raymond Veldhuis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5308)

Abstract

Fuzzy extractor is a powerful but theoretical tool to extract uniform strings from discrete noisy data. Before it can be used in practice, many concerns need to be addressed in advance, such as making the extracted strings renewable and dealing with continuous noisy data. We propose a primitive fuzzy embedder as a practical replacement for fuzzy extractor. Fuzzy embedder naturally supports renewability because it allows a randomly chosen string to be embedded. Fuzzy embedder takes continuous noisy data as input and its performance directly links to the property of the input data. We give a general construction for fuzzy embedder based on the technique of Quantization Index Modulation (QIM) and derive the performance result in relation to that of the underlying QIM. In addition, we show that quantization in 2-dimensional space is optimal from the perspective of the length of the embedded string. We also present a concrete construction for fuzzy embedder in 2-dimensional space and compare its performance with that obtained by the 4-square tiling method of Linnartz, et al. [13].

Keywords

Noisy Data Background Distribution Voronoi Region Biometric Template Physical Uncloneable Function 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Barron, R.J., Chen, B., Wornell, G.W.: The duality between information embedding and source coding with side information and some applications. IEEE Transactions on Information Theory 49(5), 1159–1180 (2003)MathSciNetCrossRefzbMATHGoogle Scholar
  2. 2.
    Boyen, X.: Reusable cryptographic fuzzy extractors. In: Atluri, V., Pfitzmann, B., McDaniel, P.D. (eds.) ACM Conference on Computer and Communications Security, pp. 82–91. ACM, New York (2004)Google Scholar
  3. 3.
    Buhan, I., Doumen, J., Hartel, P.H., Veldhuis, R.N.J.: Fuzzy extractors for continuous distributions. In: Deng, R., Samarati, P. (eds.) Proceedings of the 2nd ACM Symposium on Information, Computer and Communications Security (ASIACCS), pp. 353–355. ACM, New York (2007)CrossRefGoogle Scholar
  4. 4.
    Chang, Y.J., Zhang, W., Chen, T.: Biometrics-based cryptographic key generation. In: International Conference on Multimedia and Expo (ICME), pp. 2203–2206. IEEE, Los Alamitos (2004)Google Scholar
  5. 5.
    Chen, B., Wornell, G.W.: Quantization Index Modulation Methods for Digital Watermarking and Information Embedding of Multimedia. The Journal of VLSI Signal Processing 27(1), 7–33 (2001)CrossRefzbMATHGoogle Scholar
  6. 6.
    Chen, B., Wornell, G.W.: Dither modulation: a new approach to digital watermarking and information embedding. In: Proceedings of SPIE, vol. 3657, p. 342 (2003)Google Scholar
  7. 7.
    Chen, C., Veldhuis, R.N.J., Kevenaar, T.A.M., Akkermans, A.H.M.: Multi-bits biometric string generation based on the likelyhood ratio. In: IEEE conference on Biometrics: Theory, Applications and Systems, pp. 1–6. IEEE, Los Alamitos (2007)Google Scholar
  8. 8.
    Dodis, Y., Reyzin, L., Smith, A.: Fuzzy extractors: How to generate strong keys from biometrics and other noisy data. In: Cachin, C., Camenisch, J.L. (eds.) EUROCRYPT 2004. LNCS, vol. 3027, pp. 523–540. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  9. 9.
    Gersho, A.: Principles of quantization. IEEE Transactions on Circuits and Systems 25(7), 427–436 (1978)CrossRefGoogle Scholar
  10. 10.
    Gersho, A.: Asymptotically optimal block quantization. IEEE Transactions on Information Theory 25(4), 373–380 (1979)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Kabatiansky, G.A., Levenshtein, V.I.: Bounds for packings on a sphere and in space. Problemy Peredachi Informatsii 1, 3–25 (1978)MathSciNetGoogle Scholar
  12. 12.
    Li, Q., Sutcu, Y., Memon, N.: Secure sketch for biometric templates. In: Lai, X., Chen, K. (eds.) ASIACRYPT 2006. LNCS, vol. 4284, pp. 99–113. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    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, pp. 393–402. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  14. 14.
    Maurer, U.: Perfect cryptographic security from partially independent channels. In: Proceedings of the 23rd ACM Symposium on Theory of Computing (STOC), pp. 561–572. ACM Press, New York (1991)Google Scholar
  15. 15.
    Maurer, U.: Secret key agreement by public discussion. IEEE Transaction on Information Theory 39(3), 733–742 (1993)CrossRefzbMATHGoogle Scholar
  16. 16.
    Moulin, P., Koetter, R.: Data-hiding codes. Proceedings of the IEEE 93(12), 2083–2126 (2005)CrossRefGoogle Scholar
  17. 17.
    Skoric, B., Tuyls, P., Ophey, W.: Robust key extraction from physical uncloneable functions. In: Ioannidis, J., Keromytis, A., Yung, M. (eds.) ACNS 2005. LNCS, vol. 3531, pp. 407–422. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  18. 18.
    Tuyls, P., Akkermans, A., Kevenaar, T., Schrijen, G., Bazen, A., Veldhuis, R.: Practical biometric authentication with template protection. In: Kanade, T., Jain, A., Ratha, N.K. (eds.) AVBPA 2005. LNCS, vol. 3546, pp. 436–446. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  19. 19.
    Tuyls, P., Goseling, J.: Capacity and examples of template-protecting biometric authentication systems. In: Maltoni, D., Jain, A.K. (eds.) BioAW 2004. LNCS, vol. 3087, pp. 158–170. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  20. 20.
    Uludag, U., Pankanti, S., Prabhakar, S., Jain, A.K.: Biometric cryptosystems: Issues and challenges. Proceedings of the IEEE 92(6), 948–960 (2004)CrossRefGoogle Scholar
  21. 21.
    Zeger, K., Gersho, A.: Number of nearest neighbors in a euclidean code. IEEE Transactions on Information Theory 40(5), 1647–1649 (1994)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Ileana Buhan
    • 1
  • Jeroen Doumen
    • 1
  • Pieter Hartel
    • 1
  • Qiang Tang
    • 1
  • Raymond Veldhuis
    • 1
  1. 1.Faculty of EWIUniversity of TwenteThe Netherlands

Personalised recommendations