Context-based biometric key generation for Iris

Context-based biometric key generation for Iris

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In this study, a generic treatment of how to generate biometric keys from binary biometric templates is presented. A context-based analysis of iris biometric feature vectors based on which stable biometric keys are extracted is proposed. Most reliable bits in binary iris codes are detected and utilised to construct keys from fuzzy biometric data. The proposed key-generation scheme is adapted to diverse iris biometric feature extraction algorithms, evaluated on a comprehensive database and compared against existing iris biometric cryptosystems. In addition, the scheme is extended to provide fully revocable biometric keys, long enough to be applied in generic cryptosystems. Experimental results confirm the soundness of the approach.


    1. 1)
    2. 2)
      • A. Cavoukian , A. Stoianov , S.Z. Li . (2009) Biometric encryption, Encyclopedia of biometrics.
    3. 3)
    4. 4)
    5. 5)
      • Dodis, Y., Ostrovsky, R., Reyzin, L., Smith, A.: `Fuzzy extractors: how to generate strong keys from biometrics and other noisy data', Proc. Eurocrypt 2004, (LNCS, 3027), 2004, p. 523–540.
    6. 6)
      • Rathgeb, C., Uhl, A.: `Context-based texture analysis for secure revocable iris-biometric key generation', Proc. Third Int. Conf. on Imaging for Crime Detection and Prevention, ICDP’09, 2009, p. pp. 1.
    7. 7)
    8. 8)
      • Davida, G., Frankel, Y., Matt, B.: `On enabling secure applications through off-line biometric identification', Proc. IEEE, Symp. on Security and Privacy, 1998, p. 148–157.
    9. 9)
      • Davida, G., Frankel, Y., Matt, B.: `On the relation of error correction and cryptography to an off line biometric based identication scheme', Proc. WCC99, Workshop on Coding and Cryptography, 1999, p. 129–138.
    10. 10)
    11. 11)
    12. 12)
    13. 13)
      • Bringer, J., Chabanne, H., Cohen, G., Kindarji, B., Zémor, G.: `Optimal iris fuzzy sketches', Proc. First IEEE Int. Conf. on Biometrics: Theory, Applications, and Systems, 2007, p. 1–6.
    14. 14)
    15. 15)
      • Rathgeb, C., Uhl, A.: `Systematic construction of iris-based fuzzy commitment schemes', Proc., Third Int. Conf. on Biometrics ICB’09 (LNCS, 5558), 2009, p. 947–956.
    16. 16)
      • Rathgeb, C., Uhl, A.: `Adaptive fuzzy commitment scheme based on iris-code error analysis', Proc. Second European Workshop on Visual Information Processing (EUVIP’10), 2010, p. 41–44.
    17. 17)
      • Juels, A., Sudan, M.: `A fuzzy vault scheme', Proc. 2002 IEEE Int. Symp. on Information Theory, 2002, p. 408.
    18. 18)
      • Lee, Y.J., Bae, K., Lee, S.J., Park, K.R., Kim, J.: `Biometric key binding: fuzzy vault based on iris images', Proc. Second Int. Conf. on Biometrics (ICB’07), 2007, p. 800–808.
    19. 19)
      • Wu, X., Qi, N., Wang, K., Zhang, D.: `A novel cryptosystem based on iris key generation', Fourth Int. Conf. on Natural Computation (ICNC’08), 2008, p. 53–56.
    20. 20)
      • Wu, X., Qi, N., Wang, K., Zhang, D.: `An Iris cryptosystem for information security', IIH-MSP’08: Proc. Int. Conf. on Intelligent Information Hiding and Multimedia Signal Processing, 2008, p. 1533–1536.
    21. 21)
    22. 22)
      • Rathgeb, C., Uhl, A.: `Two-factor authentication or how to potentially counterfeit experimental results in biometric systems', Proc. Int. Conf. on Image Analysis and Recognition (ICIAR’10), Part II, (LNCS, 6112), 2010, p. 296–305.
    23. 23)
      • Nandakumar, K., Jain, A.K.: `Multibiometric template security using fuzzy vault', IEEE Second Int. Conf. on Biometrics: Theory, Applications, and Systems, BTAS’08, 2008, p. 1–6.
    24. 24)
      • W. Sheng , G. Howells , M. Fairhurst , F. Deravi . Template-free biometric-key generation by means of fuzzy genetic clustering. Trans. Inf. Forensics Sec. , 2 , 183 - 191
    25. 25)
      • Rathgeb, C., Uhl, A.: `Iris-biometric hash generation for biometric database indexing', Proc. Twentieth Int. Conf. on Pattern Recognition (ICPR’10), 2010, p. 2848–2851.
    26. 26)
    27. 27)
      • Stoianov, A., Kevenaar, T., van der Veen, M.: `Security issues of biometric encryption', Proc. Toronto Int. Conf. on Science and Technology for Humanity (TIC-STH), 2009, p. 34–39.
    28. 28)
    29. 29)
    30. 30)
      • Zuo, J., Ratha, N.K., Connel, J.H.: `Cancelable Iris biometric', Proc. 19th Int. Conf. on Pattern Recognition, (ICPR’08), 2008, p. 1–4.
    31. 31)
      • Hämmerle-Uhl, J., Pschernig, E., Uhl, A.: `Cancelable Iris biometrics using block re-mapping and image warping', Proc. Information Security Conf., ISC’09, (LNCS, 5735), 2009, p. 135–142.
    32. 32)
    33. 33)
      • Jain, A.K., Prabhakar, S., Hong, L., Pankanti, S.: `FingerCode: a filterbank for fingerprint representation and matching', Proc. Int. Conf. on Computer Vision and Pattern Recognition (CVPR’99), 1999, p. 2187–2187.

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