Fingerprint Biometric Template Security Schemes: Attacks and Countermeasures

  • Reza MehmoodEmail author
  • Arvind Selwal
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 597)


Biometrics is one of the most promising technologies for providing secure authentication in modern computing applications and eradicates the issues associated with the traditional authentication systems. Almost 50% of the security infrastructure comprises fingerprint biometric. As the market share of fingerprints is increasing tremendously, its security is becoming a challenge for research community. In this paper, a brief review of different fingerprint template security schemes has been presented. Moreover, various masquerade attacks on fingerprint template have been studied and their countermeasures are presented. A comparative analysis of different template security schemes based on different performance metrics like FAR, FRR, and EER is also provided. It was seen that the methods employed for fingerprint may not work for other biometric traits like iris, face, etc., because of their difference in dimensions of templates. This paper allows to find the research gaps in the existing template security algorithms and suggests further development in the field of biometric template protection.


Biometrics Fingerprint Template security Feature vector 


  1. 1.
    Mwema, J., Kimwele, M., Kimani, S.: A simple review of biometric template protection schemes used in preventing adversary attacks on biometric fingerprint templates. 20, 12–18 (2015). ISSN: 2231-2803Google Scholar
  2. 2.
    Selwal, A., Gupta, S.K.: Fuzzy analytic hierarchy process based template data analysis of multimodal biometric conceptual designs. Procedia Comput. Sci. 85, 899–905 (2016)Google Scholar
  3. 3.
    Jain, A.K., Ross, A. A., Nandakumar, K.: Introduction to Biometrics (Google eBook), p. 311 (2011)Google Scholar
  4. 4.
    Ratha, N.K., Connell, J.H., Bolle, R.M.: An analysis of minutiae matching strength. In: International Conference on Audio- and Video-Based Biometric Person Authentication, pp. 223–228 (2001)Google Scholar
  5. 5.
    Nandakumar, K., Jain, A.K., Nagar, A.: Biometric template security. EURASIP J. Adv. Signal Process. (2008)Google Scholar
  6. 6.
    Barman, S., Das, A.K., Member, S., Samanta, D.: Provably Secure Multi-Server Authentication Protocol using Fuzzy Commitment. IEEE Access PP, 1 (2018)Google Scholar
  7. 7.
    Selwal, A., Gupta, S.K.: Low overhead octet indexed template security scheme for multi-modal biometric system. J. Intell. Fuzzy Syst. 32, 3325–3337 (2017)Google Scholar
  8. 8.
    Jin, Z., Lai, Y., Hwang, J.Y., Kim, S., Teoh, A.J.: Ranking Based Locality Sensitive Hashing Enabled Cancelable Biometrics: Index-of-Max Hashing, 6013 (2017)Google Scholar
  9. 9.
    Gomez-Barrero, M., Galbally, J., Morales, A., Fierrez, J.: Privacy-Preserving Comparison of Variable-Length Data With Application to Biometric Template Protection, vol. 5 (2017)Google Scholar
  10. 10.
    Kaur, M., Sofat, S.: Fuzzy Vault Template Protection for Multimodal Biometric System, pp. 1131–1135 (2017)Google Scholar
  11. 11.
    Kaur, M.: Secure Fingerprint Fuzzy Vault Using Hadamard Transformation to Defy Correlation Attack (2016)Google Scholar
  12. 12.
    Sarala, S.M., Karki, M.V., Yadav, D.S.: Blended Substitution Attack Independent Fuzzy Vault for Fingerprint Template Security (2016)Google Scholar
  13. 13.
    Lafkih, M., Lacharme, P., Rosenberger, C., Mikram, M., Ghouzali, S.: Vulnerabilities of Fuzzy Vault Schemes Using Biometric Data with Traces, pp. 822–827 (2015)Google Scholar
  14. 14.
    Dang, T.K., Nguyen, M.T., Truong, Q.H.: Chaff Point Generation Mechanism for Improving Fuzzy Vault Security, pp. 147–153 (2015)Google Scholar
  15. 15.
    Feng, Y.C., Lim, M.H., Yuen, P.C.: Masquerade attack on transform-based binary-template protection based on perceptron learning. Pattern Recognit. 47, 3019–3033 (2014)CrossRefGoogle Scholar
  16. 16.
    Prasad, M.V.N.K., Santhosh Kumar, C.: Fingerprint template protection using multiline neighboring relation. Expert Syst. Appl. 41, 6114–6122 (2014)Google Scholar
  17. 17.
    Moujahdi, C., Bebis, G., Ghouzali, S., Rziza, M.: Fingerprint shell: secure representation of fingerprint template. Pattern Recognit. Lett. 45, 189–196 (2014)CrossRefGoogle Scholar
  18. 18.
    Chin, Y.J., Ong, T.S., Teoh, A.B.J., Goh, K.O.M.: Integrated biometrics template protection technique based on fingerprint and palmprint feature-level fusion. Inf. Fusion 18, 161–174 (2014)CrossRefGoogle Scholar
  19. 19.
    Mihailescu, M.I.: New enrollment scheme for biometric template using hash chaos-based cryptography. Procedia Eng. 69, 1459–1468 (2014)CrossRefGoogle Scholar
  20. 20.
    Nguyen, T.H., Wang, Y., Nguyen, T.N., Li, R.: A Fingerprint Fuzzy Vault Scheme Using a Fast Chaff Point Generation Algorithm (2013)Google Scholar
  21. 21.
    Jin, Z., Jin Teoh, A.B., Ong, T.S., Tee, C.: Fingerprint template protection with minutiae-based bit-string for security and privacy preserving. Expert Syst. Appl. 39, 6157–6167 (2012)Google Scholar
  22. 22.
    Bhatnagar, G., Wu, Q.M.J., Raman, B.: Biometric template security based on watermarking. Procedia Comput. Sci. 2, 227–235 (2010)CrossRefGoogle Scholar
  23. 23.
    Cappelli, R., Lumini, A., Maio, D., Maltoni, D.: Evaluating Minutiae Template Vulnerability, pp. 174–179 (2007)Google Scholar
  24. 24.
    Jain, A.K., Ross, A., Uludag, U.: Biometric template security: challenges and solutions. In: Secure Watermarking Multimedia, vol. 4675, pp. 629–640 (2002)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer Science and Information TechnologyCentral University of JammuJammu and KashmirIndia

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