Advertisement

Cancelable Palmprint Feature Generation Method Based on Minimum Signature

  • Jian Qiu
  • Hengjian LiEmail author
  • Xiyu Wang
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1113)

Abstract

With the emphasis on biometric privacy protection, this paper proposes a method for generating cancelable palmprint features based on minimum signature. Firstly, orthogonal features of ROI of palmprint are extracted. In order to realize a layer of security and cancelability of palmprint features, a chaotic matrix is randomly generated as the key, and then xor orthogonal features form the initial feature matrix. Then the signature matrix is generated by generating hash function randomly. The initial value of signature matrix is infinite. The initial feature matrix is scanned and calculated by using the generated hash function, and the larger value in the original signature matrix is replaced by the minimum value to form a final signature matrix as a cancelable palmprint feature stored in the database. Experiments and theoretical analysis prove that the scheme can maintain high recognition performance and effectively protect the privacy of palmprint.

Keywords

Cancelable palmprint Privacy protection Minimum signature 

References

  1. 1.
    Leng, L., Teoh, A.B.J.: Alignment-free row-co-occurrence cancelable palmprint Fuzzy Vault. Pattern Recogn. 48(7), 2290–2303 (2015)CrossRefGoogle Scholar
  2. 2.
    Ratha, N., Connell, J., Bolle, R.: Enhancing security and privacy in biometrics-based authentication systems. IBM Syst. J. 40(3), 614–634 (2001)CrossRefGoogle Scholar
  3. 3.
    Quan, F., Fei, S., Anni, C., Feifei, Z.: Cracking cancelable fingerprint template of Ratha. In: International Symposium on Computer Science & Computational Technology. IEEE (2008)Google Scholar
  4. 4.
    Juels, A., Wattenberg, M.: A Fuzzy commitment scheme. In: Proceeding of 6th ACM Conference on Computer and Communications Security, pp. 28–36 (1999)Google Scholar
  5. 5.
    Umer, S., Dhara, B.C., Chanda, B.: A novel cancelable iris recognition system based on feature learning techniques. Inf. Sci. 406–407, 102–118 (2017)CrossRefGoogle Scholar
  6. 6.
    Dwivedi, R., Dey, S., Singh, R.: A privacy-preserving cancelable iris template generation scheme using decimal encoding and look-up table mapping. Comput. Secur. 65, 373–386 (2017)CrossRefGoogle Scholar
  7. 7.
    Rathgeb, C., Breitinger, F., Busch, C.: Alignment-free cancelable iris biometric templates based on adaptive bloom filters. In: Proceedings of ICB, pp. 1–8 (2013)Google Scholar
  8. 8.
    Sadhya, D., Singh, S.K.: Providing robust security measures to Bloom filter based biometric template protection schemes. Comput. Secur. 67, 59–72 (2017)CrossRefGoogle Scholar
  9. 9.
    Bringer, J., Morel, C., Rathgeb, C.: Security analysis and improvement of some biometric protected templates based on Bloom filters. Image Vis. Comput. 58, 239–253 (2017)CrossRefGoogle Scholar
  10. 10.
    Wang, S., Hu, J.: A blind system identification approach to cancelable fingerprint templates. Pattern Recogn. 54, 14–22 (2016)CrossRefGoogle Scholar
  11. 11.
    Wang, S., Yang, W., Hu, J.: Design of alignment-free cancelable fingerprint templates with zoned minutia Pairs. Pattern Recogn. 66, 295–301 (2017)CrossRefGoogle Scholar
  12. 12.
    Alam, B., Jin, Z., Yap, W.S.: An alignment-free cancelable fingerprint template for bio-cryptosystems. J. Netw. Comput. Appl. 115, 20–32 (2018)CrossRefGoogle Scholar
  13. 13.
    Li, H., Zhang, J., Zhang, Z.: Generating cancelable palmprint templates via coupled nonlinear dynamic filters and multiple orientation palmcodes. Inf. Sci. 180(20), 3876–3893 (2010)CrossRefGoogle Scholar
  14. 14.
    Jin, Z., Lai, Y.L., Hwang, J.Y.: Ranking based locality sensitive hashing enabled cancelable biometrics: index-of-max hashing. IEEE Trans. Inf. Forensics Secur. 13(2), 393–407 (2017)CrossRefGoogle Scholar
  15. 15.
    Zhang, D., Zuo, W., Yue, F.: A comparative study of palmprint recognition algorithms. ACM Comput. Surv. 44, 2–38 (2012)CrossRefGoogle Scholar
  16. 16.
    Zhang, D., Kong, W.K., You, J., Wong, M.: Online palmprint identification. IEEE Trans. Pattern Anal. Mach. Intel. 25, 1041–1050 (2003)CrossRefGoogle Scholar
  17. 17.
    Fei, L., Xu, Y., Zhang, D.: Half-orientation extraction of palmprint features. Pattern Recogn. Lett. 69, 35–41 (2016)CrossRefGoogle Scholar
  18. 18.
    Li, H., Zhang, J., Wang, L.: Robust palmprint identification based on directional representations and compressed sensing. Multimed. Tools Appl. 70(3), 2331–2345 (2014)CrossRefGoogle Scholar
  19. 19.
    Chai, Z., Sun, Z., Méndez-Vázquez, H., He, R., Tan, T.: Gabor ordinal measures for face recognition. IEEE Trans. Inf. Forensics Secur. 9(1), 14–26 (2014)CrossRefGoogle Scholar
  20. 20.
    Rathgeb, C., Uhl, A.: A survey on biometric cryptosystems and cancelable biometrics. EURASIP J. Inf. Secur. 2011(1), 3 (2011)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Information Science and EngineeringUniversity of JiNanJinanChina

Personalised recommendations