Skip to main content
Log in

An Improved Revocable Fuzzy Vault Scheme for Face Recognition Under Unconstrained Illumination Conditions

  • Research Article - Electrical Engineering
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

The paper presents an improved fuzzy vault approach for face recognition under unconstrained environments. First, we parameterize the number of chaff points needed and determine the threshold separating the genuine points from the chaff points in the vault. The second improvement consists of enhancing the security of the fuzzy vault. Clancy et al. (in: Proceedings of ACM SIGMM2003, 2003) and Mihailescu (in: Computer Vision and Pattern Recognition (cs.CV); Cryptography and Security (cs.CR), 2007) discussed brute-force attacks to prove the weaknesses of the popular Juels and Sudan fuzzy vault method for some parameters such as the total number of points in the vault. To remedy such limitations, we introduce a cancellable and revocable biometric approach for face recognition based on the local binary patterns histograms. In addition to the revocability of the biometric data, we also achieved very recognition accuracy of more than 95% outperforming many of the exiting biometric approaches. More importantly, the proposed approach is developed to secure biometric data and achieve excellent recognition accuracy even under unconstrained environments.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Ross, A.: Information fusion in fingerprint authentication. Ph.D. Thesis, Michigan State University (2003)

  2. Ratha, N.K.; Connell, J.H.; Bolle, R.M.: An analysis of minutiae matching strength. In: Proceedings AVBPA 2001, Third International Conference on Audio- and Video-Based Biometric Person Authentication, pp. 223–228 (2001)

  3. Oppliger, R.: Contemporary Cryptography. Computer Security Series. Artech House, Boston (2005)

    MATH  Google Scholar 

  4. Riccio, D.; Galdi, C.; Manzo, R.: Biometric/cryptographic keys binding based on function minimization. In: 12th International Conference on Signal-Image Technology & Internet-Based Systems (2016). https://doi.org/10.1109/sitis.2016.31

  5. Catuogno, L.; Galdi, C.; Riccio, D.: Off-line enterprise rights management leveraging biometric key binding and secure hardware. J. Ambient Intell. and Humanized Computing, pp. 1–12 (2018)

  6. Juels, A.; Sudan, M.: A fuzzy vault scheme. In: Proceedings of IEEE International Symposium on Information Theory, p. 408 (2002)

  7. Ojala, T.; Pietikäinen, M.; Harwood, D.: A comparative study of texture measures with classification based on feature distributions. Pattern Recognit. 29(1), 51–59 (1996)

    Article  Google Scholar 

  8. Wang, Y.; Plataniotis, K.N.: Fuzzy vault for face based cryptographic key generation. In: Biometrics Symposium, 2007 E-ISBN: 978-1-4244-1549-6, Date of Conference: 11–13 Sept. 2007, pp. 1–6 (2007)

  9. Goh, A.; Ngo, D.C.L.: Computation of cryptographic keys from face biometrics. In: International Federation for Information Processing, pp. 1–13 (2003)

  10. Linnartz, J.P.; Tuyls, P.: New shielding functions to enhance privacy and prevent misuse of biometric templates In: Proceedings 4th International Conference on Audio- and Video-Based Biometric Person Authentication, pp. 393–402 (2003)

  11. Davida, G.I.; Frankel, Y.; Matt, B.J.: On enabling secure applications through on-line biometric identification. In: Proceeding of IEEE Symposium on Privacy and Security, pp. 148–157 (1998)

  12. Juels, A.; Wattenberg, M.: A fuzzy commitment scheme. In: IEEE International Symposium on Information Theory, pp. 408–413 (2002)

  13. Clancy, T.C.; Kiyavash, N.; Lin, D.J.: Secure smartcard based fingerprint authentication. In: Proceedings of ACM SIGMM2003, pp. 45–52 (2003)

  14. Yang, S.; Verbauwhede, I.: Automatic secure fingerprint verification system based on fuzzy vault scheme. In: Proceedings of International Conference on Acoustic, Speech and Signal Processing (2005)

  15. Uludag, U.; Jain, A.K.: Securing fingerprint template: fuzzy vault with helper data. In: Proceedings IEEE Workshop on Privacy Research in Vision, p. 163, June 22 (2006)

  16. Nandakumar, K.; Jain, A.K.; Pankanti, S.: Fingerprint-based fuzzy vault: implementation. IEEE Trans. Inf. Forensico Secur. 2(4), 744–757 (2007)

    Article  Google Scholar 

  17. Nagar, A.; Nandakumar, K.; Jain, A.K.: Securing fingerprint template fuzzy vault with minutiae descriptors. 19th Int. Conf. Patt. Rec., pp. 1–4 (2008)

  18. Nagar, A.; Nandakumar, K.; Jain, A.K.: Technical Report: Multibiometric Cryptosystems. IEEE TIFTS (under review)

  19. Meenakshi, V.S.; Padmavathi, G.: Securing revocable iris and retinal templates using combined user and soft biometric based password hardened multimodal fuzzy vault. IJCSI Int. J. Comput. Sci. Issues 7(5), 159–167 (2010)

    Google Scholar 

  20. Linh Vo, T.T.; Dang, T.K.; Küng, J.: A Hash-Based Index Method for Securing Biometric Fuzzy Vaults, pp. 60–71. LNCS 8647Springer International Publishing, Bern (2014)

    Google Scholar 

  21. Bao Le, T.T.; Dang, T.K.; Truong, Q.C.; Nguyen, T.A.T.: Protecting Biometric Features by Periodic Function-Based Transformation and Fuzzy Vault, pp. 57–70. LNCS 8960Springer, Berlin (2014)

    Google Scholar 

  22. Tams, B.: Unlinkable minutiae-based fuzzy vault for multiple fingerprints. IET Biometr. 5(3), 170–180 (2015)

    Article  Google Scholar 

  23. Nguyen, T.H.; Wang, Y.; Ha, Y.; Li, R.: Performance and security-enhanced fuzzy vault scheme based on ridge features for distorted fingerprints. IET Biometr. 4(1), 29–39 (2015)

    Article  Google Scholar 

  24. Kasaei, S.; Deriche, M.; Boashash, B.: Fingerprint feature extraction using block-direction on reconstructed images. In: Proceedings of IEEE TENCON ‘97. IEEE Region 10 Annual Conference. vol. 1, pp. 303–306, Brisbane, Australia (1997)

  25. Khandelwal, S.; Gupta, P.C.: Protecting biometric features by periodic function-based transformation and fuzzy vault. In: Satapathy, S.C., et al. (eds.) Emerging ICT for Bridging the Future, vol. 1311. Springer International Publishing, Bern (2015)

    Google Scholar 

  26. Hadid, A.; Ahonen, T.; Pietikäinen, M.: Computer Vision Using Local Binary Patterns, vol. 40. Springer, Berlin (2011)

    MATH  Google Scholar 

  27. Ojala, T.; Pietikäinen, M.; Mäenpää, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 971–987 (2002)

    Article  MATH  Google Scholar 

  28. Wua, L.; Yuana, S.: A face based fuzzy vault scheme for secure online authentication. In: Second International Symposium on Data, Privacy, and E-Commerce (2010)

  29. Laboratories Cambridge, ORL face database. www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html.

  30. Ahonen, T.; Pietikäinen, M.: Pixelwise local binary pattern models of faces using kernel density estimation. In ICB, pp. 52–61 (2009)

  31. Rodriguez, Y.: Face detection and verification using local binary patterns. Ph.D. Thesis at, la faculté des sciences et techniques de l’ingénieur, Ecole Polytechnique Fédérale de Lausanne, Suisse (2006)

  32. Boutellaa, E.; Bengherabi, M.; Boulkenafet, Z.; Harizi, F.; Hadid, A.: Face verification using local binary patterns generic histogram adaptation and Chi square based decision. In: 4th European Workshop on Visual Information Processing (EUVIP), pp. 142–147 (2013)

  33. Lu, H.; Martin, K.; Bui, F.; Plataniotis, K.N.; Hatzinakos, D.: Face recognition with biometric encryption for privacy-enhancing self-exclusion. In: Digital Signal Processing (2009)

  34. Martin, K.; Lu, H.; Minhthang Bui, F.; Plataniotis, K.N.; Hatzinakos, D.: A biometric encryption system for the self-exclusion scenario of face recognition. Syst. J. IEEE 3(4), 440–450 (2009)

    Article  Google Scholar 

  35. Sapkal, S.; Shrishrimal, P.; Deshmukh, R.R.: Face verification using scale invariant feature transform with template security. In: Fuzzy Systems (FUZZ-IEEE) (2017)

  36. Krizaj, J., Struc, V.; Pavesic, N.: Adaptation of SIFT features for robust face recognition. In: ICIAR 2010, Part I, LNCS 6111, pp. 394–404 (2010)

  37. Geng, C.; Jiang, X.: Face recognition using SIFT features. In: ICIP’09 Proceedings of the 16th IEEE International Conference on Image Processing, pp. 3277–3280 (2009)

  38. Lenc, L.; Král, P.: Automatic face recognition system based on the SIFT features. Comput. Electr. Eng. 46, 256–272 (2015)

    Article  Google Scholar 

  39. Ameen, M.M.; Eleyan, A.: Score fusion of SIFT & SURF descriptors for face recognition using wavelet transforms. J. Image Graph. Signal Process. 10, 22–28 (2017). https://doi.org/10.5815/ijigsp.2017.10.03

    Article  Google Scholar 

  40. Shruti Biswal, M.: Feature extraction of face using various techniques. B.Tech. thesis, National Institute of Technology Rourkela, Rourkela, India

  41. Nithya, B.; Bhavani Sankari, Y.; Manikantan, K.; Ramachandran, S.: Discrete orthonormal Stockwell transform based feature extraction for pose invariant face recognition. In: International Conference on Advanced Computing Technologies and Applications (ICACTA-2015) (2015)

  42. Anand, B.; Shah, P.K.: Face recognition using SURF features and SVM classifier. Int. J. Electron. Eng. Res. 8(1), 1–8 (2016)

    Google Scholar 

  43. Du, G.; Su, F.; Cai, A.: Face recognition using SURF features. In: MIPPR 2009: Pattern Recognition and Computer Vision, Proceedings of SPIE vol. 7496, 749628. https://doi.org/10.1117/12.832636

  44. Vinay, A.; Vasuki, V.; Bhat, S.; Jayanth, K.S.; Balasubramanya Murthy, K.N.; Natarajan, S.: Two dimensionality reduction techniques for SURF based face recognition. In: International Conference on Computational Modeling and Security (CMS 2016) (2016)

  45. Ahonen, T.; Hadid, A.; Pietikäinen, M.: Face description with local binary patterns: application to face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 28(12), 2037–2041 (2006)

    Article  MATH  Google Scholar 

  46. Werghi, N.; Tortorici, C.; Berretti, S.; Del Bimbo, A.: Boosting 3D LBP-based face recognition by fusing shape and texture descriptors on the mesh. IEEE Trans. Inf. Forensics Secur. 11(5), 964–979 (2016)

    Article  Google Scholar 

  47. Mihailescu, P.: The fuzzy vault for fingerprints is vulnerable to brute force attack. In: Computer Vision and Pattern Recognition (cs.CV); Cryptography and Security (cs.CR), 22 Aug 2007 (2007)

  48. Khalil-hani, M.; Marsono, M.N.; Bakhteri, R.: Biometric encryption based on a fuzzy vault scheme with a fast chaff generation algorithm. Fut. Gener. Comput. Syst. 29(3), 800–810 (2013)

    Article  Google Scholar 

Download references

Acknowledgements

This work has been partially supported by KFUPM under DSR project no. SB151001.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohamed Deriche.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ferhaoui Cherifi, C., Deriche, M. & Hidouci, KW. An Improved Revocable Fuzzy Vault Scheme for Face Recognition Under Unconstrained Illumination Conditions. Arab J Sci Eng 44, 7203–7217 (2019). https://doi.org/10.1007/s13369-019-03916-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-019-03916-5

Keywords

Navigation