Skip to main content
Log in

A novel cancellable Iris template generation based on salting approach

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

The iris has been vastly recognized as one of the powerful biometrics in terms of recognition performance, both theoretically and empirically. However, traditional unprotected iris biometric recognition schemes are highly vulnerable to numerous privacy and security attacks. Several methods have been proposed to generate cancellable iris templates that can be used for recognition; however, these templates achieve lower accuracy of recognition in comparison to traditional unprotected iris templates. In this paper, a novel cancellable iris recognition scheme based on the salting approach is introduced. It depends on mixing the original binary iris code with a synthetic pattern using XOR operation. This scheme guarantees a high degree of privacy/security preservation without affecting the performance accuracy compared to the unprotected traditional iris recognition schemes. Comprehensive experiments on various iris image databases demonstrate similar accuracy to those of the original counterparts. Hence, robustness to several major privacy/security attacks is guaranteed.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

References

  1. Aeloor D, Manjrekar AA (2013) Securing biometric data with visual cryptography and steganography. Springer-Verlag, Berlin Heidelberg

    Book  Google Scholar 

  2. Afifi M (2019) 11K hands: gender recognition and biometric identification using a large dataset of hand images. Multimed Tools Appl 78:20835–20854

    Article  Google Scholar 

  3. Al-Saqqa S, Al-Rawi M, Al-Zoubi MB (2013) Iris recognition system evaluation experiments using CASIA Version3, Journal of American Science

  4. Choudhury B, Then P, Raman V, Issac B, Haldar MK (2016) Cancelable Iris biometrics based on data hiding schemes. IEEE Student Conference on Research and Development

  5. Daemen J, Rijmen V (2002) AES Proposal: The Rijndael Block Cipher, tech. rep., Proton World Int.l, KatholiekeUniversiteit Leuven, ESAT-COSIC, Belgium

  6. Daugman J (1993) High confidence visual recognition of persons by a test of statistical Independence. IEEE Trans Pattern Anal Mach Intell 15(11):1148–1161

    Article  Google Scholar 

  7. Dong J, Tan T (2008) Effects of Watermarking on Iris Recognition Performance”, In: Proc. 10th Int. Conf. Control, Automation, Robotics and Vision, pp. 1156–1161

  8. Dwivedi R (2015) Cancelable Iris template generation using look-up table mapping, Research gate

  9. Essam M, Elnaby MA, Fikri M, Abd El-Samie FE (2012) A Fast Accurate Algorithm for Iris Localization Using a Coarse-to-Fine Approach, IEEE Japan-Egypt Conference on Electronics, Communications and Computer

  10. Ghoradkar S, Shinde A (2015) Review on image encryption and decryption using AES algorithm. international journal of computer applications (0975–8887), National Conference on Emerging Trends in Advanced Communication Technologies

  11. Hammerle-Uhl J, Pschernig E, Uhl A (2009) Cancelable Iris biometrics using block re-mapping and image warping. International Conference on Information Security, Pisa, pp 135–142

    Google Scholar 

  12. Jain AK, Ross A, Prabhakar S (2004) An introduction to biometric recognition. IEEE Transaction on Circuits and Systems for Video Technology 14(1):4–20

    Article  Google Scholar 

  13. Jegede A, Abdullah N, Mahmod R (2018) Revocable and non-invertible multibiometric template protection based on matrix transformation. Pertanika Journal of Science and Technology 26(1):133–160

    Google Scholar 

  14. Khan MK, Zhang J, Tian L (2004) Protecting Biometric Data for Personal Identification. Springer-Verlag, Berlin Heidelberg

    Book  Google Scholar 

  15. Lai Y, Jin Z, Teoh ABJ, Goi B, Yap W, Chai TY, Rathgeb C (2017) Cancelable Iris template generation based on indexing-first-one hashing. Pattern Recogn 64:105–117

    Article  Google Scholar 

  16. Lee D-H, Lee SH, Cho NI (2018) Cancelable biometrics using noise embedding. 24th International Conference on Pattern Recognition (ICPR), Beijing

    Book  Google Scholar 

  17. Lim S, Lee K, Byeon O, Kim T (2001) Efficient Iris recognition through improvement of feature vector and classifier. ETRI J 23(2):61–70

    Article  Google Scholar 

  18. Liu Y, Ling J, Liu Z, Shen J, Gao C (2017) “Finger vein secure biometric template generation based on deep learning”, soft computing - a fusion of foundations, Methodologies and Applications, January

  19. Nalavade R (2012) Secure Biometric Authentication Using Recursive Visual Cryptography. Int J Sci Res Publ 2(2)

  20. Ortega M, Marino C, Penedo MG, Blanco M, Gonzalez F (2006) Biometric Authentication Using Digital Retinal Images”, Proceedings of the 5th WSEAS International Conference on Applied Computer Science, Hangzhou, China, pp. 422–427

  21. Ouda O, Tsumura N, Nakaguchi T (2010) A reliable Tokenless cancelable biometrics scheme for protecting IrisCodes. IEICE Trans Inf Syst E93-D:1878–1888

    Article  Google Scholar 

  22. Patel VM, Ratha NK, Chellappa R Cancelable biometrics, IEEE Signal Processing Magazine, September 2015

  23. Pillai JK, Patel VM, Chellappa R, Ratha NK (2011) Secure and robust Iris recognition using random projections and sparse representations. IEEE Trans Pattern Anal Mach Intell 30(9):1877–1893

    Article  Google Scholar 

  24. Ratha N, Chikkerur S, Connell J, Bolle R (2007) Generating cancelable fingerprint templates. IEEE Trans Pattern Anal Mach Intell 29(4):561–572

    Article  Google Scholar 

  25. Ratha NK, Connel JH, Bolle R (2001) Enhancing security and privacy in biometrics-based authentication systems. IBM Syst J 40(3):614–634

    Article  Google Scholar 

  26. Rathgeb C, Breitinger F, Baier H, Busch C (2015) Towards Bloom filter-based indexing of iris biometric data, 15th IEEE International Conference on Biometrics, pp. 422–429

  27. Rathgeb C, Breitinger F, Busch C, Baier H (2014) On the application of bloom filters to Iris biometrics. IET Biometrics 3:207–218

    Article  Google Scholar 

  28. Savvides M, Kumar B, Khosla P (2004) Cancelable Biometric Filters for Face Recognition. Proc Int Conf Pattern Recognition 3:922–925

    Article  Google Scholar 

  29. Selvapandian A, Manivannan K (2018) Fusion Based Glioma Brain Tumor Detection and Segmentation Using ANFIS Classification, Computer Methods and Programs in Biomedicine 166, pp. 33–38

  30. Soliman RF, Amin M, Abd El-Samie FE (2018) A Modified Cancelable Biometrics Scheme Using Random Projection”, Springer-Verlag GmbH Germany, Annals of Data Science

  31. Soliman RF, Amin M, Abd El-Samie FE (2019) On mixing Iris-codes, Springer Nature Switzerland AG

  32. Soliman R, El Banby G, Elsheikh M, Abd El-Samie FE (2018) Double Random Phase Encoding for Cancelable Face and Iris Recognition. Appl Opt 57(35)

  33. Soliman R, Ramadan N, El-Khamy S, Abd El-Samie FE (2018) Efficient Cancelable Iris Recognition Scheme Based on Modified Logistic Map, Proceedings of the National Academy of Sciences, India - Section A

  34. Tarek M, Ouda O, Hamza T (2016) Robust cancelable biometrics scheme based on neural networks. IET J Biom 5(3):220–228

    Google Scholar 

  35. Tarek M, Ouda O, Hamza T (2017) Pre-image Resistant Cancelable Biometrics Scheme UsingBidirectional Memory Model. Int J Netw Secur 19(4):498–506

    Google Scholar 

  36. U. S. Government's Biometric Consortium. (http://www.biometrics.org/html/introduction.html).

  37. Umer S, Dhara BC, Chanda B (2017) A novel cancelable Iris recognition system based on feature learning techniques. Inf Sci 406–407:102–118

    Article  Google Scholar 

  38. Wen W (2008) AES Encryption Algorithm Analysis and Security Study. Computer Applications of Petroleum 16(2)

  39. Zhao D, Fang S, Xiang J , Tian J, Xiong S (2018) Iris Template Protection Based on Local Ranking, Hindawi Security and Communication Networks Vol. 2018, Article ID 4519548

  40. Zuo J, Ratha NK, Connel JH (2008) Cancelable Iris Biometric. 19th International Conference on Pattern Recognition, Tampa, pp 1–4

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zeinab F. Elsharkawy.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Asaker, A.A., Elsharkawy, Z.F., Nassar, S. et al. A novel cancellable Iris template generation based on salting approach. Multimed Tools Appl 80, 3703–3727 (2021). https://doi.org/10.1007/s11042-020-08663-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-020-08663-6

Keywords

Navigation