Cluster Computing

, Volume 22, Supplement 5, pp 12817–12825 | Cite as

Security analysis of prealigned fingerprint template using fuzzy vault scheme

  • D. Chitra
  • V. SujithaEmail author


Biometric systems accumulate information from biometric elements of an individual and used to exceptionally confirm the person with the physical and behavioral properties of the biometric characteristic. Biometrics and cryptography systems have been identified as the two main components of digital security system. Cryptography is combined with biometric to achieve high security. In this paper, fingerprint template protection is proposed which is based on fuzzy vault scheme. Initially, enrolled fingerprint images are preprocessed using some image processing techniques and preprocessed images are prealigned automatically using directed reference point. All the minutiae points are extracted and extracted minutiae features along with secret key are used to produce the fuzzy vault. Query features are given as an input with the stored template to recover the corresponding key. The proposed method is validated on FVC 2002 database. Simulation results prove that the proposed method can achieve high genuine acceptance rate with improved security.


Biometrics Bio cryptosystems Brute force attack Correlation attack Fingerprint Fuzzy vault 


  1. 1.
    Liu, H., Sun, D., Xiong, K., Zhengding, Q.: Palm print based multidimensional fuzzy vault scheme. Sci. World J. 2014, 8 (2014)Google Scholar
  2. 2.
    Arakala, A., Jeffers, J., Horadam, K.J.: Fuzzy Extractors for Minutiae-based Fingerprint Authentication. In: Lee, S.W., Li, S.Z. (eds.) Advances in Biometrics. ICB 2007. Lecture Notes in Computer Science. Springer, Berlin (2007)Google Scholar
  3. 3.
    Juels, A., Sudan, M.: A fuzzy vault scheme. In: Proceedings of the IEEE International Symposium on Information Theory, pp. 408 (2002)Google Scholar
  4. 4.
    Juels, A., Wattenberg, M.: Fuzzy commitment scheme. In: Proceedings of the ACM Conference on Computer and Communications Security (ACMCCS ’99), pp. 28–36 (1999)Google Scholar
  5. 5.
    Sapkal, S., Deshmukh, R.: Biometric template protection with fuzzy vault and fuzzy commitment. In: Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies, ACM, pp. 1–6. (2016)
  6. 6.
    Hidano, S., Tetsushi, O., Takahashi, K.: Evaluation of security for biometric guessing attacks in biometric cryptosystem using fuzzy commitment scheme. In: Proceedings of the International Conference of the Biometrics Compendium, Darmstadt, Germany. pp. 1–6 (2012)Google Scholar
  7. 7.
    Nandakumar, K., Jain, A.K., Pankanti, S.: Fingerprint based fuzzy vault: implementation and performance. IEEE Trans. Inf. Forensics Secur. 2(4), 744–757 (2007)CrossRefGoogle Scholar
  8. 8.
    Tam, B., Mihăilescu, P., Munk, A.: Security considerations in minutiae-based fuzzy vaults. IEEE Trans. Inf. Forensics Secur. 10(5), 985–998 (2015)CrossRefGoogle Scholar
  9. 9.
    Wang, Y., Plataniotis, K.N.: Fuzzy vault for face based cryptographic key generation. In: Proceedings of the Biometrics Symposium (BSYM ’07), (2007)Google Scholar
  10. 10.
    Lee, Y.J., Park, K.R., Lee, S.J., Bae, K., Kim, J.: A new method for generating an invariant iris private key based on the fuzzy vault system. IEEE Trans. Syst. Man Cybern. B 38(5), 1302–1313 (2008)CrossRefGoogle Scholar
  11. 11.
    Kumar, L.R., Kumar, S.S., Prasad, J.R., et al.: Fingerprint minutia match using bifurcation technique. Int. J. Comput. Sci. Commun. Netw. 2(4), 478–486 (2012)Google Scholar
  12. 12.
    Bhowmik, P., Bhowmik, K., Azam, M.N., Rony, M.W.: Fingerprint image enhancement and its feature extraction for recognition. Int. J. Sci. Technol. Res. 1(5), 117–121 (2012)Google Scholar
  13. 13.
    Joshua, A., Kwan, P., Gao, J.: Fingerprint Matching Using a Hybrid Shape and Orientation Descriptor. In: Jucheng, Y. (ed.) State of the Art in Biometrics. InTech, London (2011)Google Scholar
  14. 14.
    Hatano, T., Adachi, T., Shigematsu, S., Morimura, H., Onishi, S., Okazaki, Y., Kyuragi, H.: A fingerprint verification algorithm using the differential matching rate. In: Proceedings of the 16th International Conference on Pattern Recognition (2002)Google Scholar
  15. 15.
    Lindoso, A., Entrena, L., Liu Jimenez, J., San Millan, E.: Correlation-based fingerprint matching with orientation field alignment. In: Proceedings of the International conference on Biometrics, pp. 713–721 (2007)Google Scholar
  16. 16.
    Jain, A.K., Nandakumar, K., Nagar, A.: Biometric template security. EURASIP J. Adv. Signal Process. 2008, 17 (2008). Article ID579416CrossRefGoogle Scholar
  17. 17.
    Chopra, J., Upadhyay, D.P.: Various fingerprint enhancements and matching technique. Int. J. Electron. Commun. Eng. 5(3), 279–289 (2012)Google Scholar
  18. 18.
    Tams, B.: Absolute fingerprint pre-alignment in minutiae-based cryptosystems. In: Proceedings of the of BIOSIG, pp. 75–86 (2013)Google Scholar
  19. 19.
    Hanoon, M.F.: Contrast fingerprint enhancement based on histogram equalization followed by bit reduction of vector quantization. Int. J. Comput. Sci. Netw. Secur. 11(5), 116–123 (2011)Google Scholar
  20. 20.
    Barnouti, N.H.: Fingerprint recognition improvement using histogram equalization and compression methods. Int. J. Eng. Res. Gener. Sci. 4(2), 685–692 (2016)Google Scholar
  21. 21.
    Uludag, U., Jain, A.K.: Securing fingerprint template: fuzzy vault with helper data. In: Proceedings of CVPR Workshop Privacy Research Vision, New York, pp. 163 (2006)Google Scholar
  22. 22.
    Nagar, A., Nandakumar, K., Jain, A.K.: Securing fingerprint template: fuzzy vault with minutiae descriptors. In: Proceedings of the International Conference for Pattern Recognition, Tampa, pp. 1–4 (2008)Google Scholar
  23. 23.
    Tatar, F., Machhout, M.: Improvement of the fingerprint recognition process. Int. J. Bioinform. Biosci. 7(2), 1–16 (2017)Google Scholar
  24. 24.
  25. 25.
    Carneiro, R.F.L., Bessa, J.A., de Moraes, J.L., et al.: Techniques of binarization, thinning and feature extraction applied to a fingerprint system. Int. J. Comput. Appl. 103(10), 1–8 (2014)Google Scholar
  26. 26.
    Singh, R., Shah, U., Gupta, V.: Fingerprint recognition. Student project, Department of Computer Science and Engineering, Indian Institute of Technology, Kanpur, India (2009)Google Scholar
  27. 27.
    Maio, D., Maltoni, D., Cappelli, R., Wayman, J., Jain, A.: FVC2002: second fingerprint verification competition. In: Proceedings of the International Conference on Pattern Recognition, pp. 811–814 (2002)Google Scholar
  28. 28.
    Li, P., Yang, X., Cao, K., Tao, X., Wang, R., Tian, J.: An alignment free fingerprint cryptosystem based on fuzzy vault scheme. J. Netw. Comput. Appl. 33, 207–220 (2010)CrossRefGoogle Scholar
  29. 29.
    Meenakshia, V.S., Padmavathi, G.: Security analysis of password hardened multimodal biometric fuzzy vault. Int. J. Comput. Elect. Autom. Control Inf. Eng. 56, 312–320 (2009)Google Scholar
  30. 30.
    Meenakshia, V.S., Padmavathi, G.: Security analysis of password hardened multimodal biometric fuzzy vault with combined feature points extracted from fingerprint, iris and retina for high security applications. Proc. Comput. Sci. 2, 195–206 (2010)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of CSEP. A. College of Engineering and TechnologyPollachiIndia

Personalised recommendations