Skip to main content
SpringerLink
Log in

Multi-modal compound biometric feature set security and person authentication using cancelable 2D color barcode pattern generation technique

  • Original Research
  • Published:
International Journal of Information Technology Aims and scope Submit manuscript

Abstract

This paper introduces the concept of two-dimensional (2D) color barcode, also known as color quick response (QR) pattern generation, and integration as an automatic method to produce the cancelable biometric template with improved recognition accuracy. It includes various methodologies for multi-modal based generation of biometric template, cipher conversion, diversity, irreversible property, etc. In this work, based on application of different attributes to four different biometric traits combining feature selection and fusion techniques, subsequently three templates are generated. However, in general, cancelable biometrics(CB) come with some systematic template distortion, which directly depends on input biometric characteristics to protect sensitive information. This will degrade the system performance when input deals with multiple biometric traits in the multi-biometric system. To address these issues, with the notion of color variant QR pattern analysis, dynamic constrained random key generation is introduced to generate CB templates. These templates can replace all other existing CB systems without compromising the quality metrics due to an independent transformation model for an authentication factor.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Leonard DC, Pons AP, Asfour SS (2009) Realization of a universal patient identifier for electronic medical records through biometric technology. IEEE Trans Inf Technol Biomed 13(4):494–500. https://doi.org/10.1109/TITB.2008.926438

    Article  Google Scholar 

  2. Obaidat MS, Rana SP, Maitra T, Giri D, Dutta S (2019) Biometric security and Internet of Things (IoT). In: Obaidat M, Traore I, Woungang I (eds) Biometric-based physical and cybersecurity systems. Springer, Cham. https://doi.org/10.1007/978-3-319-98734-7

    Chapter  Google Scholar 

  3. Khan MK, Zhang J, Wang X (2008) Chaotic hash-based fingerprint biometric remote user authentication scheme on mobile devices. Chaos Solitons Fractals 35(3):519–524. https://doi.org/10.1016/j.chaos.2006.05.061

    Article  Google Scholar 

  4. Masdari M, Ahmadzadeh S (2017) A survey and taxonomy of the authentication schemes in telecare medicine information systems. J Netw Comput Appl 87:1–19. https://doi.org/10.1016/j.jnca.2017.03.003

    Article  Google Scholar 

  5. Reid DA, Samangooei S, Chen C, Nixon MS, Ross A (2013) Soft biometrics for surveillance: an overview. Handbook of statistics, 31st edn. Elsevier, Amsterdam, pp 327–352. https://doi.org/10.1016/B978-0-444-53859-8.00013-8

    Chapter  Google Scholar 

  6. Mishra A (2010) Multi-modal biometrics it is: need for future systems. Int J Comput Appl 3(4):28–33. https://doi.org/10.5120/720-1012

    Article  Google Scholar 

  7. Rodrigues RN, Ling LL, Govindaraju V (2009) Robustness of multi-modal biometric fusion methods against spoof attacks. J Vis Lang Comput 20(3):169–179. https://doi.org/10.1016/j.jvlc.2009.01.010

    Article  Google Scholar 

  8. Rathgeb C, Uhl A (2011) A survey on biometric cryptosystems and cancelable biometrics. EURASIP J Inf Secur 1:3. https://doi.org/10.1186/1687-417X-2011-3

    Article  Google Scholar 

  9. Canuto AM, Pintro F, Xavier-Junior JC (2013) Investigating fusion approaches in multi-biometric cancellable recognition. Expert Syst Appl 40(6):1971–1980. https://doi.org/10.1016/j.eswa.2012.10.002

    Article  Google Scholar 

  10. Canuto AMP, Pintro F, Fairhurst MC (2015) Genetic algorithm and ensemble systems for multi-biometric cancellable recognition. J Biometr Appl 1(1):101

    Google Scholar 

  11. Jain AK, Vailaya A (1996) Image retrieval using color and shape. Pattern Recogn 29(8):1233–1244. https://doi.org/10.1016/0031-3203(95)00160-3

    Article  Google Scholar 

  12. Mingqiang Y, Kidiyo K, Joseph R (2008) A survey of shape feature extraction techniques. Pattern Recogn 15(7):43–90. https://doi.org/10.5772/6237

    Article  Google Scholar 

  13. Kabbai L, Abdellaoui M, Douik A (2019) Image classification by combining local and global features. Vis Comput 35(5):679–693. https://doi.org/10.1007/s00371-018-1503-0

    Article  Google Scholar 

  14. Belguechi R, Hafiane A, Cherrier E, Rosenberger C (2016) Comparative study on texture features for fingerprint recognition: application to the biohashing template protection scheme. J Electron Imaging 25(1):013033. https://doi.org/10.1117/1.JEI.25.1.013033

    Article  Google Scholar 

  15. Toli CA, Preneel B (2014) A survey on multi-modal biometrics and the protection of their templates. IFIP international summer school on privacy and identity management. Springer, Cham, pp 169–184. https://doi.org/10.1007/978-3-319-18621-4_12

    Chapter  Google Scholar 

  16. Choudhary SK, Naik AK (2019) Multi-modal biometric authentication with secured templates-a review. Int Conf Trends Electron Inf. https://doi.org/10.1109/ICOEI.2019.8862563

    Article  Google Scholar 

  17. Ross AA, Nandakumar K, Jain AK (2006) Handbook of multi-biometrics, 6th edn. Springer Science and Business Media, Berlin

    Google Scholar 

  18. Singh M, Singh R, Ross A (2019) A comprehensive overview of biometric fusion. Inf Fus 52:187–205. https://doi.org/10.1016/j.inffus.2018.12.003

    Article  Google Scholar 

  19. Gomez-Barrero M, Maiorana E, Galbally J, Campisi P, Fierrez J (2017) Multi-biometric template protection based on homomorphic encryption. Pattern Recogn 67:149–163. https://doi.org/10.1016/j.patcog.2017.01.024

    Article  Google Scholar 

  20. Modak SKS, Jha VK (2019) Multibiometric fusion strategy and its applications: a review. Inf Fus 49:174–204. https://doi.org/10.1016/j.inffus.2018.11.018

    Article  Google Scholar 

  21. El-Sayed AYMAN (2015) Multi-biometric systems: a state of the art survey and research directions. Int J Adv Comput Sci Appl. https://doi.org/10.14569/IJACSA.2015.060618

    Article  Google Scholar 

  22. Sandhya M, Prasad MV (2017) Securing fingerprint templates using fused structures. IET Biometr 6(3):173–182. https://doi.org/10.1049/iet-bmt.2016.0008

    Article  Google Scholar 

  23. Sandhya M, Prasad MV (2018) Multi-algorithmic cancelable fingerprint template generation based on weighted sum rule and T-operators. Pattern Anal Appl 21(2):397–412. https://doi.org/10.1007/s10044-016-0584-5

    Article  MathSciNet  Google Scholar 

  24. Kumar MM, Prasad MV, Raju USN (2020) BMIAE: blockchain-based multi-instance Iris authentication using additive ElGamalhomomorphic encryption. IET Biometr 9(4):165–177. https://doi.org/10.1049/iet-bmt.2019.0169

    Article  Google Scholar 

  25. Umer S, Dhara BC, Chanda B (2016) Texture code matrix-based multi-instance iris recognition. Pattern Anal Appl 19(1):283–295. https://doi.org/10.1007/s10044-015-0482-2

    Article  MathSciNet  Google Scholar 

  26. Walia GS, Jain G, Bansal N, Singh K (2019) Adaptive weighted graph approach to generate multi-modal cancelable biometric templates. IEEE Trans Inf Forensics Secur 15:1945–1958. https://doi.org/10.1109/TIFS.2019.2954779

    Article  Google Scholar 

  27. Kaur H, Khanna P (2018) Random distance method for generating unimodal and multi-modal cancelable biometric features. IEEE Trans Inf Forensics Secur 14(3):709–719. https://doi.org/10.1109/TIFS.2018.2855669

    Article  Google Scholar 

  28. Gupta K, Walia GS, Sharma K (2021) Novel approach for multi-modal feature fusion to generate cancelable biometric. Vis Comput 37(6):1401–1413. https://doi.org/10.1007/s00371-020-01873-x

    Article  Google Scholar 

  29. Kaur H, Khanna P (2016) Biometric template protection using cancelable biometrics and visual cryptography techniques. Multimed Tools Appl 75(23):16333–16361. https://doi.org/10.1007/s11042-015-2933-6

    Article  Google Scholar 

  30. Nafea O, Ghouzali S, Abdul W, Qazi EUH (2016) Hybrid multi-biometric template protection using watermarking. Comput J 59(9):1392–1407. https://doi.org/10.1093/comjnl/bxv107

    Article  Google Scholar 

  31. Morampudi MK, Veldandi S, Prasad MV, Raju USN (2020) Multi-instance iris remote authentication using private multi-class perceptron on malicious cloud server. Appl Intell 50(9):2848–2866. https://doi.org/10.1007/s10489-020-01681-9

    Article  Google Scholar 

  32. Tarek M, Ouda O, Hamza T (2016) Robust cancellable biometrics scheme based on neural networks. IET Biometr 5(3):220–228. https://doi.org/10.1049/iet-bmt.2015.0045

    Article  Google Scholar 

  33. Wu SC, Chen PT, Swindlehurst AL, Hung PL (2018) Cancelable biometric recognition with ECGs: subspace-based approaches. IEEE Trans Inf Forensics Secur 14(5):1323–1336. https://doi.org/10.1109/TIFS.2018.2876838

    Article  Google Scholar 

  34. Sudhakar T, Gavrilova M (2020) Cancelable biometrics using deep learning as a cloud service. IEEE Access 8:112932–112943. https://doi.org/10.1109/ACCESS.2020.3003869

    Article  Google Scholar 

  35. Talreja V, Valenti MC, Nasrabadi NM (2020) Deep hashing for secure multi-modal Biometrics. IEEE Trans Inf Forensics Secur 16:1306–1321. https://doi.org/10.1109/TIFS.2020.3033189

    Article  Google Scholar 

  36. Murakami T, Fujita R, Ohki T, Kaga Y, Fujio M, Takahashi K (2019) Cancelable permutation-based indexing for secure and efficient biometric identification. IEEE Access 7:45563–45582. https://doi.org/10.1109/ACCESS.2019.2908456

    Article  Google Scholar 

  37. Bousnina N, Ghouzali S, Mikram M, Abdul W (2019) DTCWT-DCT watermarking method for multi-modal biometric authentication. Proc Int Conf Netw Inf Syst Secur. https://doi.org/10.1145/3320326.3320409

    Article  Google Scholar 

  38. Bousnina N, Ghouzali S, Mikram M, Lafkih M, Nafea O, Al-Razgan M, Abdul W (2021) Hybrid multi-modal biometric template protection. Intell Autom Soft Comput 27(1):35–51. https://doi.org/10.32604/iasc.2021.014694

    Article  Google Scholar 

  39. RzougaHaddada L, Amara EBN (2019) Double watermarking-based biometric access control for radio frequency identification card. Int J RF Microw Comput Aided Eng 29(11):e21905. https://doi.org/10.1002/mmce.21905

    Article  Google Scholar 

  40. Selwal A, Gupta SK, Kumar S (2016) A scheme for template security at feature fusion level in multi-modal biometric system. Adv Sci Technol Res J. https://doi.org/10.12913/22998624/64062

    Article  Google Scholar 

  41. Kaur M, Sofat S (2017) Fuzzy vault template protection for multi-modal biometric system. Int Conf Comput Commun Autom (ICCCA). https://doi.org/10.1109/CCAA.2017.8229966

    Article  Google Scholar 

  42. Yang W, Wang S, Hu J, Zheng G, Valli C (2018) A fingerprint and finger-vein based cancelable multi-biometric system. Pattern Recogn 78:242–251. https://doi.org/10.1016/j.patcog.2018.01.026

    Article  Google Scholar 

  43. Rajbhoj SM, Mane PB (2014) Match score integration of iris and fingerprint in multi-biometrics system. Int Conf Electr Commun Syst (ICECS). https://doi.org/10.1109/ECS.2014.6892564

    Article  Google Scholar 

  44. Yang J, Zhang X (2012) Feature-level fusion of fingerprint and finger-vein for personal identification. Pattern Recogn Lett 33(5):623–628. https://doi.org/10.1016/j.patrec.2011.11.002

    Article  Google Scholar 

  45. Gawande U, Golhar Y (2018) Biometric security system: a rigorous review of unimodal and multi-modal biometrics techniques. Int J Biometr 10(2):142–175. https://doi.org/10.1504/IJBM.2018.10012749

    Article  Google Scholar 

  46. Rachapalli DR, Kalluri HK (2019) Disseminating the authentication process based on secure RGVSS multi-biometric template encryption through QR code in health care informatics. Int J Emerg Technol 10(3):370–378

    Google Scholar 

  47. Rachapalli DR, Kalluri HK (2017) A survey on biometrie template protection using cancelable biometric scheme. Second Int Conf Electr Comput Commun Technol (ICECCT). https://doi.org/10.1109/ICECCT.2017.8117828

    Article  Google Scholar 

  48. Rachapalli DR, Kalluri HK (2018) Texture driven hierarchical fusion for multi-biometric system. Int J Eng Technol 7(4):33–37. https://doi.org/10.14419/ijet.v7i4.24.21766

    Article  Google Scholar 

  49. Rachapalli DR, Kalluri HK (2020) Color QR Pattern-Driven Cancelable Biometric Fingerprint System. Ingénierie des Syst Inf 25(2):245–251. https://doi.org/10.18280/isi.250212

    Article  Google Scholar 

  50. https://www.thonky.com/qr-code-tutorial. Accessed 2 June 2021

  51. Center for Biometrics and Security Research. http://biometrics.idealtest.org/download-CASIA-Iris-Interval. Accessed 17 Apr 2021

  52. Center for Biometrics and Security Research. http://biometrics.idealtest.org/CASIA-Palmprint. Accessed 16 Apr 2021

  53. Cappelli R, Ferrara M, Franco A, Maltoni D (2007) Fingerprint verification competition 2006. Biometr Technol Today 15(7–8):7–9. https://doi.org/10.1016/S0969-4765(07)70140-6

    Article  Google Scholar 

  54. Martinez AM, Kak AC (2001) Pca versus lda. IEEE Trans Pattern Anal Mach Intell 23(2):228–233. https://doi.org/10.1109/34.908974

    Article  Google Scholar 

  55. Patil P, Jagtap S (2020) Multi-modal biometric system using finger knuckle image and retina image with template security using PolyU and DRIVE database. Int J Inf Technol 12(4):1043–1050. https://doi.org/10.1007/s41870-020-00501-0

    Article  Google Scholar 

  56. Jagadiswary D, Saraswady D (2016) Biometric authentication using fused multi-modal biometric. Proced Comput Sci 85:109–116. https://doi.org/10.1016/j.procs.2016.05.187

    Article  Google Scholar 

  57. Sujatha E, Chilambuchelvan A (2018) Multi-modal biometric authentication algorithm using iris, palm print, face and signature with encoded dwt. Wirel Pers Commun 99(1):23–34. https://doi.org/10.1007/s11277-017-5034-1

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, SriKalahasteeswara Institute of Technology, Srikalahasti, Andhra Pradesh, India

    Devendra Reddy Rachapalli

  2. Department of Computer Science and Engineering, Vignan’s Foundation for Science,Technology and Research University (Deemed to be University), Guntur, Andhra Pradesh, India

    Hemantha Kumar Kalluri

Authors
  1. Devendra Reddy Rachapalli
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hemantha Kumar Kalluri
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Devendra Reddy Rachapalli.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rachapalli, D.R., Kalluri, H.K. Multi-modal compound biometric feature set security and person authentication using cancelable 2D color barcode pattern generation technique. Int. j. inf. tecnol. 14, 201–214 (2022). https://doi.org/10.1007/s41870-021-00819-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41870-021-00819-3

Keywords

Search

Navigation