IJIGSP Vol. 12, No. 5, 8 Oct. 2020
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Biometric Templates, Cancelable biometrics, Biometric cryptosystem Arnold Transformation, Bio-hashing, Fingerprint.
Fingerprint biometric is popularly used for protecting digital devices and applications. They are better and more reliable for authentication in comparison to the usual security tokens or password, which make them to be at the forefront of identity management systems. Though, they have several security benefits, there are several weaknesses of the fingerprint biometric recognition system. The greatest challenge of the fingerprint biometric system is theft or leakage of the template information. Also, each individual has limited and unique fingerprint which is permanent throughout their lifespan, hence, the compromise of the fingerprint biometric will cause a lifetime threat to the security and privacy of such an individual. Security and privacy risk of fingerprint biometric have previously been studied in the context of cryptosystem and cancelable biometric generation. However, these approaches do not obviously address the issue of revocability, diversity and irreversibility of fingerprint features to guard against the wrong use or theft of fingerprint biometric information. In this paper, we proposed a model that harnesses the strength of Arnold transform and Bio-hashing on fingerprint biometric features to overcome the limitations commonly encountered in sole fingerprint biometric approaches. In the experimental analysis, the result of irreversibility showed 0% False Acceptance Rate (FAR), performance showed maximum of 0.2% FAR and maximum of 0.8% False Rejection Rate (FRR) at different threshold values. Also, the result of renewability/revocability at SMDKAB SMKADKB and SMKBDKA showed that the protection did not match each other. Therefore, the performance of the proposed model was notable and the techniques could be efficiently and reliably used to enforce protection on biometric templates in establishments/organizations so that their information and processes could be secured.
Olufade F. W. Onifade, Kabirat B. Olayemi, Folasade O. Isinkaye, " A Fingerprint Template Protection Scheme Using Arnold Transform and Bio-hashing", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.12, No.5, pp. 28-36, 2020. DOI: 10.5815/ijigsp.2020.05.03
[1]V.K. Gunjan, P.S. Prasad, and S. Mukherjee, “Biometric template protection scheme-cancelable biometrics.” In ICCCE 2019 (pp. 405-411). Springer, Singapore
[2]M. Arjunwadkar, R. V. Kulkarni and C. Shahu, “Biometric Device Assistant Tool: Intelligent Agent for Intrusion Detection at Biometric Device using JESS,” International Journal of Computer Science Issues, 2012, Vol. 9, no. 6, pp. 366-370.
[3]N. K. Ratha, J. H. Connell, R. M. Bolle, “Enhancing security and privacy in biometrics-based authentication systems.” IBM systems Journal, 2001, Vol.40, no. 3, pp. 614-634.
[4]M. Kaur, S. Sofat and D. Saraswat, “Template and Database Security in Biometric Systems: A Challenging Task,” International Journal of Computer Applications, 2010, Vol. 4, no. 5, pp.1-5.
[5]P. Poongodi, and P. Betty, “A Study on Biometric Template Protection Techniques.” International Journal of Engineering Trends and Technology (IJETT), 2014, Vol.7, no. 4, pp. 202-204.
[6]M. Butt, O. Henniger, A. Nouak, A. and Kuijper, “Privacy protection of biometric templates,” In International Conference on Human-Computer Interaction, 2014, (pp. 153-158). Springer, Cham.
[7]V. Sujitha and D. Chitra, “Highly secure palmprint based biometric template using fuzzy vault.” Concurrency and Computation: Practice and Experience, 2019, Vol. 31, no. 12, e4513.
[8]R. Mehmood, and A. Selwal, “Fingerprint biometric template security schemes: attacks and countermeasures.” In Proceedings of ICRIC 2019 (pp. 455-467). Springer, Cham.
[9]A. Selwal, and S.K Gupta, “Template security analysis of multimodal biometric frameworks based on fingerprint and hand geometry.” Perspectives in Science, Vol. 8, pp. 705-708.
[10]F. O. Isinkaye, J. Soyemi, and O. I. Arowosegbe, (2020). An Android-based Face Recognition System for Class Attendance and Malpractice Control. International Journal of Computer Science and Information Security (IJCSIS), 2020, Vol. 18, no.1, pp.78-83.
[11]O. F. Onifade, P. Akinde, and F. O. Isinkaye, Circular Gabor wavelet algorithm for fingerprint liveness detection. Journal of Advanced Computer Science & Technology, 2020, Vol. 9 no.1, pp.1-5.
[12]N. M.Surse, and P. Vinayakray-Jani, “Finger-vein template protection using compressed sensing.” In Innovations in Computer Science and Engineering, 2019, (pp. 299-307). Springer, Singapore.
[13]G. Mehta, M. K. Dutta, J. Karasek, and P. S. Kim, “An efficient and lossless fingerprint encryption algorithm using Henon map & Arnold transformation.” In 2013 International Conference on Control Communication and Computing (ICCC), 2013, (pp. 485-489). IEEE.
[14]G. Mehta, M. K. Dutta, and P. S. Kim, “A secure encryption method for biometric templates based on chaotic theory.” In Transactions on Computational Science XXVII, 2016, (pp. 120-140). Springer, Berlin, Heidelberg.
[15]D. S Wang, J. P. Li, D. K. Hu, and Y. H. Yan, “A novel biometric image integrity authentication using fragile watermarking and Arnold transform.” In Information Computing and Automation, 2008, (In 3 Volumes) (pp. 799-802).
[16]Z. Tang, and X. Zhang, “Secure image encryption without size limitation using Arnold transform and random strategies.” Journal of multimedia, 2011, Vol. 6, no. 2, pp. 202.
[17]B. Topcu, H. Erdogan, C. Karabat, and B. Yanikoglu, “Biohashing with fingerprint spectral minutiae”. In 2013 International Conference of the BIOSIG Special Interest Group (BIOSIG), 2013, (pp. 1-12). IEEE.
[18]K. Atighehchi, L. Ghammam, M. Barbier, and C. Rosenberger, “GREYC-Hashing: Combining biometrics and secret for enhancing the security of protected templates”. Future Generation Computer Systems, 2019, Vol. 101, pp. 819-830.
[19]N. Saini, and A. Sinha, “Soft biometrics in conjunction with optics based biohashing.” Optics communications, 2011, Vol. 284, no. 3, pp. 756-763.
[20]Y. B. Huang, Y. Wang, Q. Y. Zhang, W. Z. Zhang, and M. H. Fan, (2020). “Multi-format speech BioHashing based on spectrogram.” Multimedia Tools and Applications, 2020, pp. 1-21.
[21]P. Lacharme, “Revisiting the accuracy of the biohashing algorithm on fingerprints.” IET biometrics, 2013, Vol. 2, no. 3, pp. 130-133.
[22]S. K. A. Khalid, M. M. Deris and K. M. Mohamad, “A robust digital image watermarking against salt and pepper using Sudoku,” In The Second International Conference on Informatics Engineering & Information Science (ICIEIS2013), 2013, (pp. 96-106). The Society of Digital Information and Wireless Communication.
[23]A. T. B. Jin, D. N. C. Ling and O. T. Song, “An efficient fingerprint verification system using integrated wavelet and Fourier–Mellin invariant transform,” Image and Vision Computing, 2004, Vol. 22, no. 6, pp. 503-513.
[24]P. N. Gakare, A. M. Patel, J. R. Vaghela and R. N. Awale, “Real time feature extraction of ECG signal on android platform,” In 2012 international conference on communication, information & computing technology (ICCICT), 2012, (pp. 1-5). IEEE.