Comb Filter Approach for Cancelable Face and Fingerprints Recognition

Document Type : Original Article

Authors

1 Department of Electronics and Electrical Communications Engineering Higher Institute of Engineering,Elshorok academy Egypt

2 Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia University: Menouf, Egypt

3 Department of Electronics and Electrical Communications EngineeringFaculty of Electronic EngineeringMenoufia University:Menouf, Egypt

4 Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia University:Menouf, Egypt

Abstract

Now many security systems depend on biometrics, these systems have suffered from hacking trials. If the biometric databases have been hacked and stolen, the biometrics saved in these databases will be lost forever. Thus, there is a desperate need to develop new cancelable biometric systems. The main concept of cancelable biometrics is to use another version of the original biometric template created through a one-way transform or an encryption scheme to keep the original biometrics safe and away from utilization in the system. In this paper, a comb filter algorithm is utilized for cancelable face and fingerprint recognition systems. The comb filter performs encryption process for faces and fingerprints to produce their cancelable patterns and compare them with any random attacked encrypted biometric. We notice that there is no any correlation between the stored biometrics and the attacked biometric at different filter order (L) values of the employed comb filter where L is tested in the cases of 6, 8, 10, and 12. Also, we calculate the  evaluation matrices of the Equal Error Rate (EER), False Accept Rate (FAR), False Reject Rate (FRR), and the Area under Receiver Operating Characteristic (ROC) curves for the proposed framework.

Keywords


[1]     A. K. Jain, A. A. Ross, and K. Nandakumar,“Introduction to Biometrics”, Springer ,pp. 107-130,2017.
[2]     R. Bolle, J. Connell,S.Pankanti, N. K. Ratha, A. W. Senior, “Authentication and Biometrics”, Guide to Biometrics, pp. 17-30, Springer, 2004.
[3]     D.Maltoni, AK.Jain, D.Maio, S.Prabhakar, “Handbook of Fingerprint Recognition”, Springer,ISBN 0-387-95431-7, 2004
[4]     S. Rakesh, A. A. Kaller, B. Shadakshari, and B. Annappa, “Image Encryption Using Block Based Uniform Scrambling and Chaotic Logistic Mapping”, International Journal of Cryptogr. Inf. Secur. (IJCIS), Vol. 2, No. 1, pp. 49–57, 2012.
[5]     R. Jayapal, “Biometric encryption system for increased security”, Master Degree Thesis, College of Computing, Engineering & Construction, University of North Florida, 2017.
[6]     P. Patel, M .Rajpoot, “Secure Fingerprint Identification System and Matching by Using Image Registration and Key Matching Techniques”, International Journal of Engineering Research & Technology (IJERT), Vol. 2, June 2013.
[7]     D. Cui, “A Novel Fingerprint Encryption Algorithm Based on Chaotic System and Fractional Fourier Transform”, International Conference on Machine Vision and Human-Machine Interface,DOI 10.1109/MVHI.2010.38, 2010.
[8]     S. Li and X. Zheng, “Cryptanalysis of a chaotic fingerprint encryption method”, Proceedings of The IEEE Int. Symposium on Circuits and Systems (ISCAS),DOI:10.1109/iscas.2002.1011451 , 2002.
[9]     A. Chatterjee, S. Mandal, G.M. Rahaman and A. M. Arif, “Fingerprint Identification and Verification System by Minutiae Extraction Using Artificial Neural Network”, Proceedings of The JCIT, 2010.
[10]  B. Liang, Z. Wu, and Linyou, “A Novel Fingerprint-Based Biometric Encryption”, Proceedings of The Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing,DOI: 10.1109/3PGCIC.2014.48, 2014.
[11]  V. M. Patel, N. K. Ratha, and R. Chellappa, “Cancelable biometrics: A Review”, Proceedings of The IEEE Signal Processing Magazine,vol. 32, no. 5, pp. 54-65, 2015.
[12]  H. Kaur and P. Khanna,“Non-invertible biometric encryption to generate Cancelable biometric templates”, Proceeding of the world Congress on Engineering and Computer Science, San Francisco, ISBN: 978-988-14047-5-6, 2017.
[13]  M. Tarek, O. Ouda, and T. Hamza, “Pre-image resistant cancelable biometrics scheme using bidirectional memory model”, Proceedings of The International Journal of Network Security ,DOI:10.6633/IJNS.201707.19(4).2,2017.
[14]  S. V. K. Gaddam and M. Lal, “Efficient cancelable biometric key generation scheme for cryptography”, Proceedings of The International Journal of Network Security, Vol.11, No.2, PP.61–69, Sept,2010.
[15]  Punithavathi P, Subbiah G (2017) Can cancelable biometrics preserve privacy?. Biometric Technology Today 7: 8-11
[16]  Rashid RA, Mahalin NH, Sarijari MA, Abdul Aziz AA (2008) Security system using biometric technology: Design and implementation of Voice Recognition System (VRS). In: International Conference onComputer and Communication Engineering ICCCE2008, pp. 898-902
[17]  Vezzetti E, Marcolin F (2012) Geometrical descriptors for human face morphological analysis and recognition. Robotics and Autonomous Systems 60(6), 928-939
[18]  Zuo J, Ratha NK Connell JH (2008) Cancelable iris biometric. In: 19th International Conference on Pattern Recognition ICPR2008, pp. 1-4
[19]  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
[20]  Tarek M, Ouda O, Hamza T (2017) Pre-image resistant cancelable biometrics scheme using bidirectional memory model. International Journal of Network Security 19(4): 498-506
[21]  Syarif MA, Ong TS, Teoh ABJ, Tee C (2014) Improved biohashing method based on most Intensive histogram block location. In: International Conference of Neural Information Processing, pp. 644-652
[22]  Teoh ABJ, Ngo DCL, Goh A (2004) Biohashing: two factor authentication featuring fingerprint data and tokenised random number. Pattern Recognition 37(11): 2245-2255
[23]  Arpit D,Nwogu I, Srivastava G, Govindaraju (2014) An Analysis of random projections in cancelable biometrics.  In: Proceedings of the 31st International Conference on Machine Learning vol. 32
[24]  Rathgeb C, Uhl A (2010) Secure iris recognition based on local intensity variations. In: Proceedings of the 7th International Conference on Image Analysis and Recognition II, pp. 266-275
[25]  Rathgeb C, Breitinger F, Baier H, Busch C (2015) Towards bloom filter-based indexing of iris biometric data. In: IEEE International Conference on Biometrics (ICB), pp. 422-429
[26]  Rathgeb C, Breitinger F, Busch C, Baier H (2014) On the application of bloom filters to iris biometrics. IET Journal on Biometrics 3(4): 207-218
[27]  Hermans J., Mennink B., and Peeters R., “When a Bloom filter is a Doom filter: Security assessment of a novel iris biometric template protection system”, International Conference of the Biometrics Special Interest Group (BIOSIG), pp. 1-6, 2014, Darmstadt, Germany.
[28]  Gomez-Barrero M, Rathgeb C, Galbally J, Busch C,  Fierrez J (2016) Unlinkable and irreversible biometric template protection based on bloom filters. Information Sciences 370(C): 18-32
[29]  Rahulkar AD, Holambe RS (2012) Half-iris feature extraction and recognition using a new class of biorthogonal triplet half-band filter bank and flexible k-out-of-n: A postclassifier. IEEE Transactions on Information Forensics and Security 7(1): 230–240
[30]  Ouda O, Tsumura N, Nakaguchi T (2011) On the security of bioEncoding based cancelable biometrics. IEICE Transactions on Information and System 94-D(9): 1768–1777
[31]  Ouda O, Tsumura N, Nakaguchi T (2010) A reliable tokenless cancelable biometrics scheme for protecting Iriscodes. IEICE Transactions on Information and Systems E93-D(7): 1878-1888
[32]  Lacharme P (2012) Analysis of the iriscodes bioencoding scheme. International Journal of Computer Science and Security 6(5): 315-321
[33]  Hämmerle-Uhl J, Pschernig E, Uhl A (2009) Cancelable iris biometrics using block re-mapping and image warping. In: Springer Berlin Heidelberg International Conference on Information Security, pp. 135-142
[34]  Jenisch S Uhl A (2011) Security analysis of a cancelable iris recognition system based on block remapping. In: 18th IEEE International Conference on Image Processing, pp. 3213-3216
[35]  Dwivedi R, Dey S (2015) Cancelable iris template generation using look-up table mapping. In: Signal Processing and Integrated Networks (SPIN) 2nd International Conference on Signal Processing and Integrated Network, pp. 785-790
[36]  Tarek M, Ouda O, Hamza T (2016) Robustcancelable biometrics scheme based on neural networks. The Institution of Engineering and Technology, IET Biometrics, 5(3): 220–228
[37]  Kumar A, Passi A (2010) Comparison and combination of iris matchers for reliable personal authentication. Pattern Recognition 43: 1016-1026
[38]  Lai Y, Jin J, Teoh ABJ, Goi B, Yap W, Chai T, Rathgeb, C (2017) Cancelable iris template generation based on Indexing-First-One hashing. Pattern Recognition 64: 105–117
[39]  Wan M, Li M, Yang G, Gai S, Jin Z (2014) Feature extraction using two-dimensional maximum embedding difference. Information Sciences 274:55-69
[40]  Wan M, Yang G, Gai S, Yang Z(2017) Two-dimensional discriminant locality preserving projections (2DDLPP) and its application to feature extraction via Fuzzy set. Multimedia Tools and Applications 76 (1):355-371
[41]  Wan M, Lai Z, Yang G, Yang Z, Zhang F, Zheng H (2017) Local graph embedding based on maximum margin criterion via fuzzy set. Fuzzy Sets and Systems 318: 120-131
[42]  Daugman JG (1985) Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. Optical Society of America, Journal, A: Optics and Image Science 2(7): 1160-1169.
[43]  Grigorescu S, Petkov N, Kruizinga P (2002) Comparison of texture features based on Gabor filters. IEEE Trans. Image Process. 11(10): 1160-1167.
[44]  Daugman J (2004) How iris recognition works. IEEE Trans. Circuits Syst. Video Technol. 14, 21–30.
[45]  Masek L (2003) Recognition of human iris patterns for biometric identification. M. Thesis, The University of Western Australia.
[46]  Soliman N F, Mohamed E, Magdi F, Abd El-Samie FE, AbdElnaby M (2017) Efficient iris localization and recognition. Optik - International Journal for Light and Electron Optics 140: 469-475.
[47]  [47]Burge MJ, Kevin KW (2013) Handbook of iris recognition. Springer.
[48]  Patel VM, Ratha NK, Chellappa R (2015) Cancelable biometrics: A Review. IEEE Signal Processing Magazine 32(5): 54-65.
[49]  Evans N, Marcel S, Ross A, Teoh ABJ (2015) Biometrics security and privacy protection. IEEE Signal Process Mag 32(5):17–18.
[50]  Johnson W, Lindenstrauss J (1984) Extensions of Lipschitz maps into a hilbert space. Contemporary Mathimatics 26:189–206.
[51]  Ferreira JL, Wu Y, Aarts RM (2018) Enhancement of the Comb filtering Selectivity Using Iterative Moving Average for Periodic Waveform and Harmonic Elimination. Journal of Healthcare Engineering 2018
[52]  Kuo SM, Lee BH, Tain W (2006) Real-Time signal processing, implantations and applications. John Wiley & Sons Ltd, 2nd.
[53]  CASIA-IrisV3-Database, http://www.cbsr.ia.ac.cn/english/IrisDatabase.asp. Accessed December 2017.
[54]  Jain AK, Li SZ (2005) Handbook of face recognition. Springer 1st.
[55]  Performance testing of biometric template protection scheme for reasonable performance evaluation. 2018 Information Technology, ISO/IEC 30136.
[56]  O.  Ouda, N. Tsumura, and T. Nakaguchi, “On the security of bioencoding based cancelable biometrics”, Proceedings of The IEICE Transactions on Information and Systems, vol. E94-D, no. 9, pp. 1768-1777, 2011.
[57]  Ross and A. Othman, “Mixing fingerprints for template security and privacy”, in Proc. 19th Eur. Signal Proc. Conf. (EUSIPCO), Barcelona, pp. 554-558, 2011.
 
Volume 28, ICEEM2019-Special Issue
ICEEM2019-Special Issue: 1st International Conference on Electronic Eng., Faculty of Electronic Eng., Menouf, Egypt, 7-8 Dec.
2019
Pages 89-94