Fuzzy Extractors: How to Generate Strong Keys from Biometrics and Other Noisy Data

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3027)


We provide formal definitions and efficient secure techniques for
  • turning biometric information into keys usable for any cryptographic application, and

  • reliably and securely authenticating biometric data.

Our techniques apply not just to biometric information, but to any keying material that, unlike traditional cryptographic keys, is (1) not reproducible precisely and (2) not distributed uniformly. We propose two primitives: a fuzzy extractor extracts nearly uniform randomness R from its biometric input; the extraction is error-tolerant in the sense that R will be the same even if the input changes, as long as it remains reasonably close to the original. Thus, R can be used as a key in any cryptographic application. A secure sketch produces public information about its biometric input w that does not reveal w, and yet allows exact recovery of w given another value that is close to w. Thus, it can be used to reliably reproduce error-prone biometric inputs without incurring the security risk inherent in storing them.

In addition to formally introducing our new primitives, we provide nearly optimal constructions of both primitives for various measures of “closeness” of input data, such as Hamming distance, edit distance, and set difference.


  1. 1.
    Agrell, E., Vardy, A., Zeger, K.: Upper bounds for constant-weight codes. IEEE Transactions on Information Theory 46(7), 2373–2395 (2000)zbMATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    Andoni, A., Deza, M., Gupta, A., Indyk, P., Raskhodnikova, S.: Lower bounds for embedding edit distance into normed spaces. In: Proc. ACM Symp. on Discrete Algorithms, pp. 523–526 (2003)Google Scholar
  3. 3.
    Bennett, C., Brassard, G., Robert, J.: Privacy Amplification by Public Discussion. SIAM J. on Computing 17(2), 210–229 (1988)CrossRefMathSciNetGoogle Scholar
  4. 4.
    Bennett, C., Brassard, G., Crépeau, C., Maurer, U.: Generalized Privacy Amplification. IEEE Transactions on Information Theory 41(6), 1915–1923 (1995)zbMATHCrossRefGoogle Scholar
  5. 5.
    Broder, A.: On the resemblence and containment of documents. In: Compression and Complexity of Sequences (1997)Google Scholar
  6. 6.
    Brouwer, E., Shearer, J.B., Sloane, N.J.A., Smith, W.D.: A new table of constant weight codes. IEEE Transactions on Information Theory 36, 1334–1380 (1990)zbMATHCrossRefMathSciNetGoogle Scholar
  7. 7.
    Crépeau, C.: Efficient Cryptographic Protocols Based on Noisy Channels. In: Fumy, W. (ed.) EUROCRYPT 1997. LNCS, vol. 1233, pp. 306–317. Springer, Heidelberg (1997)Google Scholar
  8. 8.
    Davida, G., Frankel, Y., Matt, B.: On enabling secure applications through offline biometric identification. In: Proc. IEEE Symp. on Security and Privacy, pp. 148–157 (1998)Google Scholar
  9. 9.
    Ding, Y.Z.: ManuscriptGoogle Scholar
  10. 10.
    Ellison, C., Hall, C., Milbert, R., Schneier, B.: Protecting Keys with Personal Entropy. Future Generation Computer Systems 16, 311–318 (2000)CrossRefGoogle Scholar
  11. 11.
    Frykholm, N.: Passwords: Beyond the Terminal Interaction Model. Master’s Thesis, Umea UniversityGoogle Scholar
  12. 12.
    Frykholm, N., Juels, A.: Error-Tolerant Password Recovery. In: Proc. ACM Conf. Computer and Communications Security, pp. 1–8 (2001)Google Scholar
  13. 13.
    Guruswami, V., Sudan, M.: Improved Decoding of Reed-Solomon and Algebraic- Geometric Codes. In: Proc. 39th IEEE Symp. on Foundations of Computer Science, pp. 28–39 (1998)Google Scholar
  14. 14.
    Håstad, J., Impagliazzo, R., Levin, L., Luby, M.: A Pseudorandom generator from any one-way function. In: Proc. 21st ACM Symp. on Theory of Computing (1989)Google Scholar
  15. 15.
    Juels, A., Wattenberg, M.: A Fuzzy Commitment Scheme. In: Proc. ACM Conf. Computer and Communications Security, pp. 28–36 (1999)Google Scholar
  16. 16.
    Juels, A., Sudan, M.: A Fuzzy Vault Scheme. In: IEEE International Symposium on Information Theory (2002)Google Scholar
  17. 17.
    Kelsey, J., Schneier, B., Hall, C., Wagner, D.: Secure Applications of Low-Entropy Keys. In: Proc. of Information Security Workshop, pp. 121–134 (1997)Google Scholar
  18. 18.
    Linnartz, J.-P.M.G., 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
  19. 19.
    van Lint, J.H.: Introduction to Coding Theory, p. 183. Springer, Heidelberg (1992)zbMATHGoogle Scholar
  20. 20.
    Monrose, F., Reiter, M., Wetzel, S.: Password Hardening Based on Keystroke Dynamics. In: Proc. ACM Conf. Computer and Communications Security, pp. 73–82 (1999)Google Scholar
  21. 21.
    Monrose, F., Reiter, M., Li, Q., Wetzel, S.: Cryptographic key generation from voice. In: Proc. IEEE Symp. on Security and Privacy (2001)Google Scholar
  22. 22.
    Monrose, F., Reiter, M., Li, Q., Wetzel, S.: Using voice to generate cryptographic keys. In: Proc. of Odyssey 2001, The Speaker Verification Workshop (2001)Google Scholar
  23. 23.
    Nisan, N., Ta-Shma, A.: Extracting Randomness: a survey and new constructions. JCSS 58(1), 148–173 (1999)zbMATHMathSciNetGoogle Scholar
  24. 24.
    Nisan, N., Zuckerman, D.: Randomness is Linear in Space. JCSS 52(1), 43–52 (1996)zbMATHMathSciNetGoogle Scholar
  25. 25.
    Radhakrishnan, J., Ta-Shma, A.: Tight bounds for depth-two superconcentrators. In: Proc. 38th IEEE Symp. on Foundations of Computer Science, pp. 585–594 (1997)Google Scholar
  26. 26.
    Shaltiel, R.: Recent developments in Explicit Constructions of Extractors. Bulletin of the EATCS 77, 67–95 (2002)zbMATHMathSciNetGoogle Scholar
  27. 27.
    Shoup, V.: A Proposal for an ISO Standard for Public Key Encryption (2001), Available at
  28. 28.
    Verbitskiy, E., Tyls, P., Denteneer, D., Linnartz, J.-P.: Reliable Biometric Authentication with Privacy Protection. In: Proc. 24th Benelux Symposium on Information theory (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  1. 1.New York University 
  2. 2.Boston University 
  3. 3.MIT 

Personalised recommendations