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Fingerprint Template Protection: From Theory to Practice

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Security and Privacy in Biometrics

Abstract

One of the potential vulnerabilities in a biometric system is the leakage of biometric template information, which may lead to serious security and privacy threats. Most of the available template protection techniques fail to meet all the desired requirements of a practical biometric system like revocability, security, privacy, and high matching accuracy. In particular, protecting the fingerprint templates has been a difficult problem due to large intra-user variations (e.g., rotation, translation, nonlinear deformation, and partial prints). There are two fundamental challenges in any fingerprint template protection scheme. First, we need to select an appropriate representation scheme that captures most of the discriminatory information, but is sufficiently invariant to changes in finger placement and can be secured using available template protection algorithms. Secondly, we need to automatically align or register the fingerprints obtained during enrollment and matching without using any information that could reveal the features, which uniquely characterize a fingerprint. This chapter analyzes how these two challenges are being addressed in practice and how the design choices affect the trade-off between the security and matching accuracy. Though much progress has been made over the last decade, we believe that fingerprint template protection algorithms are still not sufficiently robust to be incorporated into practical fingerprint recognition systems.

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Notes

  1. 1.

    A unary encoding works as follows. Suppose that a real-value a needs to be encoded using t bits. The range of a, say [a min,a max], is quantized into (t+1) bins. If a falls into the ith bin, it is represented as (t−i+1) ones followed by (i−1) zeros, where i=1,2,…,(t+1).

  2. 2.

    Given the secure sketch, leakage rate quantifies the information available to adversary about the original biometric template (known as privacy leakage) or the cryptographic key associated to it (secret key leakage).

References

  1. Andoni A, Indyk P (2008) Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. Communications of the ACM 51(1):117–122

    Article  Google Scholar 

  2. Bleichenbacher D, Nguyen PQ (2000) Noisy polynomial interpolation and noisy Chinese remaindering. In: Proc Nineteenth IACR Eurocrypt, Bruges, Belgium, pp 53–69

    Google Scholar 

  3. Boonchaiseree N, Areekul V (2009) Focal point detection based on half concentric lens model for singular point extraction in fingerprint. In: Proceedings of International Conference on Biometrics, pp 637–646

    Google Scholar 

  4. Boult TE, Scheirer WJ, Woodworth R (2007) Fingerprint revocable biotokens: accuracy and security analysis. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp 1–8

    Google Scholar 

  5. Bringer J, Chabanne H, Cohen G, Kindarji B, Zémor G (2008) Theoretical and practical boundaries of binary secure sketches. IEEE Transactions on Information Forensics and Security 3(4):673–683

    Article  Google Scholar 

  6. Cappelli R, Lumini A, Maio D, Maltoni D (2007) Fingerprint image reconstruction from standard templates. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(9):1489–1503

    Article  Google Scholar 

  7. Cappelli R, Ferrara M, Maltoni D (2010) Minutia cylinder-code: a new representation and matching technique for fingerprint recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(12):2128–2141

    Article  Google Scholar 

  8. Chang EC, Roy S (2007) Robust extraction of secret bits from minutiae. In: Proc Second International Conference on Biometrics, Seoul, South Korea, pp 750–759

    Google Scholar 

  9. Chen C, Veldhuis R (2009) Binary biometric representation through pairwise polar quantization. In: Proc International Conference on Biometrics, pp 72–81

    Google Scholar 

  10. Chen C, Veldhuis RNJ, Kevenaar TAM, Akkermans AHM (2009) Biometric quantization through detection rate optimized bit allocation. EURASIP Journal on Advances in Signal Processing

    Google Scholar 

  11. Chung Y, Moon D, Lee S, Jung S, Kim T, Ahn D (2005) Automatic alignment of fingerprint features for fuzzy fingerprint vault. In: Proc Conference on Information Security and Cryptology, Beijing, China, pp 358–369

    Chapter  Google Scholar 

  12. Clancy T, Lin D, Kiyavash N (2003) Secure smartcard-based fingerprint authentication. In: Proc ACM SIGMM Workshop on Biometric Methods and Applications, Berkley, USA, pp 45–52

    Google Scholar 

  13. Dass SC, Jain AK (2004) Fingerprint classification using orientation field flow curves. In: Proc Indian Conference on Computer Vision, Graphics and Image Processing, Kolkata, India, pp 650–655

    Google Scholar 

  14. Dodis Y, Ostrovsky R, Reyzin L, Smith A (2006) Fuzzy extractors: how to generate strong keys from biometrics and other noisy data. Tech rep 235, Cryptology ePrint archive. A preliminary version of this work appeared in EUROCRYPT 2004

    Google Scholar 

  15. Draper SC, Khisti A, Martinian E, Vetro A, Yedidia JS (2007) Using distributed source coding to secure fingerprint biometrics. In: Proc IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Hawaii, USA, vol 2, pp 129–132

    Google Scholar 

  16. Farooq F, Bolle R, Jea T, Ratha N (2007) Anonymous and revocable fingerprint recognition. In: Proc IEEE Computer Vision and Pattern Recognition

    Google Scholar 

  17. Feng J (2008) Combining minutiae descriptors for fingerprint matching. Pattern Recognition 41(1):342–352

    Article  MATH  Google Scholar 

  18. Feng J, Jain A (2009) FM model based fingerprint reconstruction from minutiae template. In: International Conference on Biometrics (ICB)

    Google Scholar 

  19. Hao F, Anderson R, Daugman J (2006) Combining crypto with biometrics effectively. IEEE Transactions on Computers 55(9):1081–1088

    Article  Google Scholar 

  20. Ignatenko T, Willems FMJ (2009) Biometric systems: privacy and secrecy aspects. IEEE Transactions on Information Forensics and Security 4(4):956–973

    Article  Google Scholar 

  21. Jain AK, Pankanti S (2006) A touch of money. IEEE Spectrum 3(7):22–27

    Article  Google Scholar 

  22. Jain AK, Hong L, Bolle R (1997) On-line fingerprint verification. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(4):302–314

    Article  Google Scholar 

  23. Jain A, Nandakumar K, Nagar A (2008) Biometric template security. EURASIP Journal on Advances in Signal Processing

    Google Scholar 

  24. Jeffers J, Arakala A (2006) Minutiae-based structures for a fuzzy vault. In: Proc Biometric Symposium, BCC, Baltimore, MD, pp 1–6

    Google Scholar 

  25. Jeffers J, Arakala A (2007) Fingerprint alignment for a minutiae-based fuzzy vault. In: Proc Biometric Symposium, BCC, Baltimore, MD

    Google Scholar 

  26. Juels A, Sudan M (2002) A fuzzy vault scheme. In: Proc IEEE International Symposium on Information Theory, Lausanne, Switzerland, p 408

    Chapter  Google Scholar 

  27. Juels A, Wattenberg M (1999) A fuzzy commitment scheme. In: Proc Sixth ACM Conference on Computer and Communications Security, Singapore, pp 28–36

    Chapter  Google Scholar 

  28. Lai L, Ho SW, Poor HV (2008) Privacy-security tradeoffs in biometric security systems. In: Annual Allerton Conference on Communication, Control, and Computing, Monticello, IL, pp 23–26

    Google Scholar 

  29. Lee C, Choi JY, Toh KA, Lee S (2007) Alignment-free cancelable fingerprint templates based on local minutiae information. IEEE Transactions on Systems, Man and Cybernetics. Part B. Cybernetics 37(4):980–992

    Article  Google Scholar 

  30. Maio D, Maltoni D, Wayman JL, Jain AK (2002) FVC2002: second fingerprint verification competition. In: Proc International Conference on Pattern Recognition (ICPR), Quebec City, Canada, pp 811–814

    Google Scholar 

  31. Maltoni D, Maio D, Jain AK, Prabhakar S (2009) Handbook of Fingerprint Recognition, 2nd edn. Springer, Berlin

    Book  Google Scholar 

  32. Nagar A, Nandakumar K, Jain AK (2008) Securing fingerprint template: fuzzy vault with minutiae descriptors. In: Proc IEEE International Conference on Pattern Recognition, Tampa, FL

    Google Scholar 

  33. Nagar A, Rane S, Vetro A (2010) Privacy and security of features extracted from minutiae aggregates. In: Proceedings IEEE International Conf on Acoustics, Speech and Signal Processing, Dallas, TX, pp 524–531

    Google Scholar 

  34. Nagar A, Rane SD, Vetro A (2010) Alignment and bit extraction for secure fingerprint biometrics. In: SPIE Conference on Electronic Imaging (Special Collection), vol 7541

    Google Scholar 

  35. Nandakumar K (2010) A fingerprint cryptosystem based on minutiae phase spectrum. In: Proc of Second IEEE Workshop on Info Forensics & Security, Seattle, USA

    Google Scholar 

  36. Nandakumar K, Jain AK, Pankanti S (2007) Fingerprint-based fuzzy vault: implementation and performance. IEEE Transactions on Information Forensics and Security 2(4):744–757

    Article  Google Scholar 

  37. Nandakumar K, Nagar A, Jain AK (2007) Hardening fingerprint fuzzy vault using password. In: Proc Second Intl Conf on Biometrics, Seoul, South Korea, pp 927–937

    Google Scholar 

  38. Nilsson K, Bigun J (2002) Complex filters applied to fingerprint images detecting prominent symmetry points used for alignment. In: Proceedings of International Conference on Biometric Authentication, pp 39–47

    Chapter  Google Scholar 

  39. Peng HC, Long F, Ding C (2005) Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(8):1226–1238

    Article  Google Scholar 

  40. Pudil P, Novovicova J, Kittler J (1994) Floating search methods in feature selection. Pattern Recognition Letters 15:1119–1125

    Article  Google Scholar 

  41. Ramo P, Tico M, Onnia V, Saarinen J (2001) Optimized singular point detection algorithm for fingerprint images. In: Proceedings of ICIP, pp 242–245

    Google Scholar 

  42. Ratha NK, Chikkerur S, Connell JH, Bolle RM (2007) Generating cancelable fingerprint templates. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(4):561–572

    Article  Google Scholar 

  43. Rhodes D (2002) Methods for binary multidimensional scaling. Neural Computation 14:1195–1232

    Article  Google Scholar 

  44. Ross AK, Shah J, Jain AK (2007) From templates to images: reconstructing fingerprints from minutiae points. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(4):544–560

    Article  Google Scholar 

  45. Scheirer WJ, Boult TE (2007) Cracking fuzzy vaults and biometric encryption. In: Proceedings of Biometrics Symposium

    Google Scholar 

  46. Scheirer W, Boult T (2008) Bio-cryptographic protocols with bipartite biotokens. In: Proc Biometric Symposium

    Google Scholar 

  47. Soutar C, Roberge D, Stoianov A, Gilroy R, Kumar BVKV (1998) Biometric encryption using image processing. In: Proc of SPIE, vol 3314, pp 178–188

    Google Scholar 

  48. Sutcu Y, Rane S, Yedidia J, Draper S, Vetro A (2008) Feature extraction for a Slepian-Wolf biometric system using ldpc codes. In: Proc the IEEE International Symposium on Information Theory, Toronto, Canada

    Google Scholar 

  49. Teoh ABJ, Toh KA, Yip WK (2007) 2N discretisation of BioPhasor in cancelable biometrics. In: Proc Second Intl Conf on Biometrics, Seoul, South Korea, pp 435–444

    Google Scholar 

  50. Tulyakov S, Farooq F, Mansukhani P, Govindaraju V (2007) Symmetric hash functions for secure fingerprint biometric systems. Pattern Recognition Letters 28(16):2427–2436

    Article  Google Scholar 

  51. Uludag U, Jain AK (2006) Securing fingerprint template: fuzzy vault with helper data. In: Proc CVPR Workshop on Privacy Research in Vision, New York, USA, p 163

    Google Scholar 

  52. Uludag U, Pankanti S, Prabhakar S, Jain AK (2004) Biometric cryptosystems: issues and challenges. Proceedings of the IEEE 92(6):948–960. Special issue on multimedia security for digital rights management

    Article  Google Scholar 

  53. Uludag U, Pankanti S, Jain AK (2005) Fuzzy vault for fingerprints. In: Proc Fifth International Conference on Audio- and Video-Based Biometric Person Authentication, Rye Town, USA, pp 310–319

    Chapter  Google Scholar 

  54. Wilson C, Hicklin AR, Bone M, Korves H, Grother P, Ulery B, Micheals R, Zoepfl M, Otto S, Watson C (2004) Fingerprint vendor technology evaluation 2003: summary of results and analysis report. Technical report NISTIR 7123, NIST

    Google Scholar 

  55. Xu H, Veldhuis RNJ, Bazen AM, Kevenaar TAM, Akkermans TAHM, Gokberk B (2009) Fingerprint verification using spectral minutiae representations. IEEE Transactions on Information Forensics and Security 4(3):397–409

    Article  Google Scholar 

  56. Yang S, Verbauwhede I (2005) Automatic secure fingerprint verification system based on fuzzy vault scheme. In: Proc IEEE International Conference on Acoustics, Speech, and Signal Processing, Philadelphia, USA, vol 5, pp 609–612

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science & Engineering, Michigan State University, East Lansing, MI, 48824, USA

    Anil K. Jain & Abhishek Nagar

  2. Department of Brain & Cognitive Engineering, Korea University, Seoul, South Korea

    Anil K. Jain

  3. Institute for Infocomm Research, A*STAR, Fusionopolis, Singapore, Singapore

    Karthik Nandakumar

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  1. Anil K. Jain
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  2. Karthik Nandakumar
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  3. Abhishek Nagar
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Correspondence to Anil K. Jain .

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Editors and Affiliations

  1. Department of Applied Electronics, Roma Tre University, via della Vasca Navale 84, Rome, 00146, Italy

    Patrizio Campisi

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Jain, A.K., Nandakumar, K., Nagar, A. (2013). Fingerprint Template Protection: From Theory to Practice. In: Campisi, P. (eds) Security and Privacy in Biometrics. Springer, London. https://doi.org/10.1007/978-1-4471-5230-9_8

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  • DOI: https://doi.org/10.1007/978-1-4471-5230-9_8

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