Private Fingerprint Matching

  • Siamak F. Shahandashti
  • Reihaneh Safavi-Naini
  • Philip Ogunbona
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7372)


We propose a fully private fingerprint matching protocol that compares two fingerprints based on the most widely-used minutia-based fingerprint matching algorithm. The protocol enables two parties, each holding a private fingerprint, to find out if their fingerprints belong to the same individual. Unlike previous works, we do not make any simplifying assumption on the matching algorithm or use generic multiparty computation protocols in our constructions. We employ a commonly-used algorithm that works by first comparing minutia pairs from the two fingerprints based on their types, locations, and orientations, and then checking if the number of matching minutia pairs is more than a threshold, and we propose a concrete, scalable, and modular protocol. We prove security against honest-but-curious adversaries and discuss how security against malicious adversaries can be achieved using standard cryptographic techniques. Our protocol is realized using common cryptographic primitives and do not require pairing- or lattice-based cryptography.


Authentication System Homomorphic Encryption Private Information Retrieval Malicious Adversary Private Input 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Barral, C., Coron, J.-S., Naccache, D.: Externalized Fingerprint Matching. In: Zhang and Jain [10], pp. 309–315Google Scholar
  2. 2.
    Blanton, M., Gasti, P.: Secure and Efficient Protocols for Iris and Fingerprint Identification. In: Atluri, V., Diaz, C. (eds.) ESORICS 2011. LNCS, vol. 6879, pp. 190–209. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  3. 3.
    Bringer, J., Chabanne, H., Izabachène, M., Pointcheval, D., Tang, Q., Zimmer, S.: An Application of the Goldwasser-Micali Cryptosystem to Biometric Authentication. In: Pieprzyk, J., Ghodosi, H., Dawson, E. (eds.) ACISP 2007. LNCS, vol. 4586, pp. 96–106. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  4. 4.
    Bringer, J., Chabanne, H., Pointcheval, D., Tang, Q.: Extended Private Information Retrieval and Its Application in Biometrics Authentications. In: Bao, F., Ling, S., Okamoto, T., Wang, H., Xing, C. (eds.) CANS 2007. LNCS, vol. 4856, pp. 175–193. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  5. 5.
    Goldwasser, S., Micali, S.: Probabilistic Encryption. J. Comput. Syst. Sci. 28(2), 270–299 (1984)MathSciNetzbMATHCrossRefGoogle Scholar
  6. 6.
    Kerschbaum, F., Atallah, M.J., M’Raïhi, D., Rice, J.R.: Private Fingerprint Verification without Local Storage. In: Zhang and Jain [10], pp. 387–394Google Scholar
  7. 7.
    Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition. Springer (2009)Google Scholar
  8. 8.
    Paillier, P.: Public-Key Cryptosystems Based on Composite Degree Residuosity Classes. In: Stern, J. (ed.) EUROCRYPT 1999. LNCS, vol. 1592, pp. 223–238. Springer, Heidelberg (1999)Google Scholar
  9. 9.
    Shahandashti, S.F., Safavi-Naini, R., Ogunbona, P.: Private Fingerprint Matching. Cryptology ePrint Archive, Report 2012/219 (2012),
  10. 10.
    Zhang, D., Jain, A.K. (eds.): ICBA 2004. LNCS, vol. 3072. Springer, Heidelberg (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Siamak F. Shahandashti
    • 1
  • Reihaneh Safavi-Naini
    • 2
  • Philip Ogunbona
    • 3
  1. 1.University of Paris 8 and École Normale SupérieureParisFrance
  2. 2.Institute for Security, Privacy, and Info. AssuranceUniversity of CalgaryCanada
  3. 3.ICT Research InstituteUniversity of WollongongAustralia

Personalised recommendations