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FinCaT: a novel approach for fingerprint template protection using quadrant mapping via non-invertible transformation

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Abstract

The employment of various technologies for secured human authentication in the recent years has led to rapid expansion of biometric-based recognition. Among all biometrics, the fingerprint recognition systems (FRS) hold the largest market share and have been used in numerous computing applications such as forensic, governance, and securing critical infrastructure. Though biometric systems provide plentiful benefits over the traditional identification systems but these are also susceptible to various adversarial attacks. The most crucial among all the attacks involves security breaches of stored templates in a central database that may either degrade the overall performance or result in a complete failure of the FRS. To countermeasure these attacks, template protection mechanisms are designed that mitigate the masquerade attacks or template thefts. In this study, we present a novel cancellable approach for fingerprint template protection (FinCaT) using the novel notion of quadrant mapping via a non-invertible transformation function. Our method transforms original fingerprint templates to highly secured templates by using quadrant mapping that maps minutia points by using distinct parameters in each quadrant. The FinCAT approach yields high revocability and diversity as the compromised template of a genuine user can be replaced with a newly generated secured template. The approach is experimentally evaluated on the FVC 2002 fingerprint benchmark dataset. Our technique demonstrates decent performance in terms of an equal error rate (EER) of 5.95% and a recognition accuracy of 94.05%, which is promising as compared to similar state-of-the art template protection techniques.

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References

  1. Abdullahi SM, Wang H, Li T (2020) Fractal coding-based robust and alignment-free fingerprint image hashing. IEEE Trans Inf Forensics Secur 15:2587–2601. https://doi.org/10.1109/TIFS.2020.2971142

    Article  Google Scholar 

  2. Ajish S, Anil Kumar KS (2020) Security and performance enhancement of fingerprint biometric template using symmetric hashing. Computers and Security 90:101714. https://doi.org/10.1016/j.cose.2020.101714

    Article  Google Scholar 

  3. Ajish S, AnilKumar KS (2023) Performance enhancement of symmetric hashed fingerprint template using dynamic threshold matching algorithm. Int J Biometrics 15(1):78–100. https://doi.org/10.1504/ijbm.2023.127726

  4. Ali SS, Ganapathi II, Prakash S (2018) Robust technique for fingerprint template protection. IET Biometrics 7(6):536–549. https://doi.org/10.1049/iet-bmt.2018.5070

    Article  Google Scholar 

  5. Ali SS, Ganapathi II, Prakash S, Consul P, Mahyo S (2020) Securing biometric user template using modified minutiae attributes. Pattern Recogn Lett 129:263–270. https://doi.org/10.1016/j.patrec.2019.11.037

    Article  Google Scholar 

  6. Atighehchi K, Ghammam L, Barbier M, Rosenberger C (2019) GREYC-hashing: combining biometrics and secret for enhancing the security of protected templates. Futur Gener Comput Syst 101:819–830. https://doi.org/10.1016/j.future.2019.07.022

    Article  Google Scholar 

  7. Bedari A, Wang S, Yang W (2021) Design of Cancelable MCC-Based Fingerprint Templates Using Dyno-Key Model. Pattern Recogn:108074. https://doi.org/10.1016/j.patcog.2021.108074

  8. Cao K, Jain AK (2015) Learning fingerprint reconstruction : from minutiae to image. IEEE Trans Inf Forensics Secur 10(1):104–117. https://doi.org/10.1109/TIFS.2014.2363951

    Article  Google Scholar 

  9. Chaurasia P, Kohli R, Garg A (2014) Biometrics minutiae detection and feature extraction. Illustrated ed. Lambert Academic Publishing, Chisinau

  10. Ferrara M, Maltoni D, Cappelli R (2012) Noninvertible minutia cylinder-code representation. IEEE Trans Inf Forensics Secur 7(6):1727–1737. https://doi.org/10.1109/TIFS.2012.2215326

    Article  Google Scholar 

  11. Gao Q, Zhang C (2017) Constructing cancellable template with synthetic minutiae. IET Biometrics 6(6):448–456. https://doi.org/10.1049/iet-bmt.2016.0192

    Article  Google Scholar 

  12. Jacob IJ, Betty P, Darney PE, Raja S, Robinson YH, Julie EG (2021) Biometric template security using DNA codec based transformation. Multimed Tools Appl 80(5):7547–7566. https://doi.org/10.1007/s11042-020-10127-w

    Article  Google Scholar 

  13. Jain AK, Nandakumar K, Nagar A (2008a) Biometric template security. EURASIP J Adv Signal Process 2008:579416. https://doi.org/10.1155/2008/579416

    Article  Google Scholar 

  14. Jain AK, Flynn P, Ross A (2008b) Handbook of biometrics, vol 2008. Springer. https://doi.org/10.1007/9780-387-71041-9

    Book  Google Scholar 

  15. Jha DP (2016). Proposed encryption algorithm for data security using matrix properties. 2016 Iciccs, 86–90. https://doi.org/10.1109/ICICCS.2016.7542316

  16. Jin Z, Jin Teoh AB, Ong TS, Tee C (2012) Fingerprint template protection with minutiae-based bit-string for security and privacy preserving. Expert Syst Appl 39(6):6157–6167. https://doi.org/10.1016/j.eswa.2011.11.091

    Article  Google Scholar 

  17. Juels A, Drive C, Wattenberg M, Street W (1999) A fuzzy commitment scheme. 6th ACM conference on computer and communications security, 28–36. https://doi.org/10.1145/319709.319714

  18. Kavati I, Reddy AM, Babu ES, Reddy KS (2021) Design of a fingerprint template protection scheme using elliptical structures. ICT Express 2021:4–7. https://doi.org/10.1016/j.icte.2021.04.001

    Article  Google Scholar 

  19. Kho JB, Kim J, Kim IJ, Teoh ABJ (2019) Cancelable fingerprint template design with randomized non-negative least squares. Pattern Recogn 91:245–260. https://doi.org/10.1016/j.patcog.2019.01.039

    Article  Google Scholar 

  20. Kho JB, Teoh ABJ, Lee W, Kim J (2020) Bit-string representation of a fingerprint image by normalized local structures. Pattern Recogn 103:107323. https://doi.org/10.1016/j.patcog.2020.107323

    Article  Google Scholar 

  21. Maio D, Maltoni D, Cappelli R, Wayman JL, Jain AK (2002) FVC2002 : Second Fingerprint Verification Competition FVC2002. Second Fingerprint Verification Competition January 2008. https://doi.org/10.1109/ICPR.2002.1048144

  22. Manzoor SI, Selwal A (2018) An analysis of biometric based security systems. 2018 fifth international conference on parallel, distributed and grid computing (PDGC), 4, 306–311. https://doi.org/10.1109/PDGC.2018.8745722

  23. Mehmood R, Selwal A (2020) Polynomial based fuzzy vault technique for template security in fingerprint biometrics. Int Arab J Inf Technol 17(6):926–934

    Google Scholar 

  24. Rajan RA, Kumaran P (2019) Fingerprint template security using angle-based transformation functions. IEEE international conference on intelligent techniques in control, optimization and signal processing, INCOS 2019. https://doi.org/10.1109/INCOS45849.2019.8951335

  25. Ratha NK, Connell JH, Bolle RM (2001) Enhancing security and privacy in biometrics-based authentication systems. IBM Syst J 40(3):614–634. https://doi.org/10.1147/sj.403.0614

    Article  Google Scholar 

  26. Ross A, Shah J, Jain AK (2005) Towards reconstructing fingerprints from minutiae points. Biometric Technology for Human Identification II, 5779, 68–80. https://doi.org/10.1117/12.604477

  27. Sarkar A, Singh BK (2021) A multi-instance cancelable fingerprint biometric based secure session key agreement protocol employing elliptic curve cryptography and a double hash function. Multimed Tools Appl 80(1):799–829. https://doi.org/10.1007/s11042-020-09375-7

    Article  Google Scholar 

  28. Sehar EU, Selwal A, Sharma D (2021) FinCaT: fingerprint cancellable template protection remediation schemes, challenges, and future directions. 2021 fourth international conference on computational intelligence and communication technologies (CCICT), 260–267. https://doi.org/10.1109/CCICT53244.2021.00056

  29. Selwal A, Gupta SK (2017) Low overhead octet indexed template security scheme for multi-modal biometric system. J Intell Fuzzy Syst 32(5):3325–3337. https://doi.org/10.3233/JIFS-169274

    Article  Google Scholar 

  30. Selwal A, Kumar S (2016) Fuzzy analytic hierarchy process based template data analysis of multimodal biometric conceptual designs. Procedia Comput Sci 85(Cms):899–905. https://doi.org/10.1016/j.procs.2016.05.280

    Article  Google Scholar 

  31. Selwal A, Gupta SK, Surender, Anubhuti (2015) Performance analysis of template data security and protection in biometric systems. 2nd international conference on recent advances in Engineering & Computational Sciences (RAECS) 2015, 1–6. https://doi.org/10.1109/RAECS.2015.7453302

  32. Shahzad M, Wang S, Deng G, Yang W (2021) Alignment-free cancelable fingerprint templates with dual protection. Pattern Recogn 111:107735. https://doi.org/10.1016/j.patcog.2020.107735

    Article  Google Scholar 

  33. Sharma D, Selwal A (2020) On data-driven approaches for presentation attack detection in iris recognition systems. In: Singh PK, Singh Y, Kolekar MH, Kar AK, Chhabra JK, Sen A (eds) Recent Innovations in Computing. ICRIC 2020, Lecture Notes in Electrical Engineering, p 701. https://doi.org/10.1007/978-981-15-8297-4_38

    Chapter  Google Scholar 

  34. Sharma D, Selwal A (2021a) An intelligent approach for fingerprint presentation attack detection using ensemble learning with improved local image features. Multimed Tools Appl 81:22129–22161. (issue 0123456789). Springer US. https://doi.org/10.1007/s11042-021-11254-8

    Article  Google Scholar 

  35. Sharma D, Selwal A (2021b) FinPAD : State-of-the-art of fingerprint presentation attack detection mechanisms, taxonomy and future perspectives. Pattern Recogn Lett 152(March 2005):225–252. https://doi.org/10.1016/j.patrec.2021.10.013

    Article  Google Scholar 

  36. Trivedi AK, Thounaojam DM, Pal S (2018) A robust and non-invertible fingerprint template for fingerprint matching system. Forensic Sci Int 288:256–265. https://doi.org/10.1016/j.forsciint.2018.04.045

    Article  Google Scholar 

  37. Trivedi AK, Thounaojam DM, Pal S (2020) Non-invertible cancellable fingerprint template for fingerprint biometric. Comput Secur 90:101690. https://doi.org/10.1016/j.cose.2019.101690

    Article  Google Scholar 

  38. Trivedi AK, Thounaojam DM, Pal S (2021) A novel minutiae triangulation technique for non-invertible fingerprint template generation. Expert Syst Appl 186:115832. https://doi.org/10.1016/j.eswa.2021.115832

    Article  Google Scholar 

  39. Uludag U, Pankanti S, Prabhakar S, Jain AK (2004) Biometric cryptosystems: issues and challenges. Proc IEEE 92(6):948–959. https://doi.org/10.1109/JPROC.2004.827372

    Article  Google Scholar 

  40. Wang S, Yang W, Hu J (2017) Design of Alignment-Free Cancelable Fingerprint Templates with zoned minutia pairs. Pattern Recogn 66:295–301. https://doi.org/10.1016/j.patcog.2017.01.019

    Article  Google Scholar 

  41. Wang S, Deng G, Hu J (2017a) A partial Hadamard transform approach to the design of cancelable fingerprint templates containing binary biometric representations. Pattern Recogn 61:447–458. https://doi.org/10.1016/j.patcog.2016.08.017

    Article  MATH  Google Scholar 

  42. Wong WJ, Teoh ABJ, Kho YH, Wong ML (2016) Kernel PCA enabled bit-string representation for minutiae-based cancellable fingerprint template. Pattern Recogn 51:197–208. https://doi.org/10.1016/j.patcog.2015.09.032

    Article  Google Scholar 

  43. Yang S, Berdine G (2017) The reciever operating characteristic (ROC) curve. Southwest Respir Crit Care Chron 5(19):34–36. https://doi.org/10.12746/swrccc.v5i19.391

    Article  Google Scholar 

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Correspondence to Eain Ul Sehar.

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Sehar, E.U., Selwal, A. & Sharma, D. FinCaT: a novel approach for fingerprint template protection using quadrant mapping via non-invertible transformation. Multimed Tools Appl 82, 22795–22813 (2023). https://doi.org/10.1007/s11042-023-14576-x

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