A fuzzy vault development based on iris images

Keywords: Authentication, Biometrics, Fuzzy vault, Iris, Template protection, GLCM, CASIA v1, ITTD v1, FAR, FRR


Biometric systems gather information from the person's biometric attributes, used extensively to authorize the individuals. Due to the obvious convenience of using specific individual traits such as face, fingerprints, palm veins, and irises, biometric authentication is becoming more common. In particular, Iris systems are in high demand for high-assurance applications, because they contain a broad feature set and remain stable. Authentication methods based on iris biometrics are now commonly used in a variety of fields. This is due to the fact that iris biometric authentication is both safer and more comfortable than conventional passwords. Template Security is a major concern in biometric systems. The template security mechanism ensures reusable, permanent, and un-linkable models. The Fuzzy Vault strategy is one of the most popular security schemes for Template protection.

Fuzzy vault has demonstrated to be an effective protection method but lacks revocability and security attacks. This article introduced an improved fuzzy vault system. The improved fuzzy vault system was introduced, which uses more than one key to protect biometric data. Different keys make the search space more detailed. The additional key was used to encrypt vault data, which stopped the intruder from accessing the information on the person's biometry. The system was tested using CASIA.v1 and IITD.v1 datasets, and findings showed that the system ensures the protection and authentication of the iris templates without compromising performance. The proposed modification gave a 0.0 % False Accepted Rate (FAR) for both the dataset and False Rejected Rate (FRR), 0.14 % for CASIA v1 and 0.12 % for ITTD v1 False Rejected rate


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Author Biographies

Mohammed A. Taha, University of Technology

Department of Computer Sciences

Hanaa M. Ahmed, University of Technology

Department of Computer Sciences


You, L., Wang, T. (2018). A novel fuzzy vault scheme based on fingerprint and finger vein feature fusion. Soft Computing, 23 (11), 3843–3851. doi: https://doi.org/10.1007/s00500-018-3046-8

Juels, A., Sudan, M. (2006). A Fuzzy Vault Scheme. Designs, Codes and Cryptography, 38 (2), 237–257. doi: https://doi.org/10.1007/s10623-005-6343-z

Reddy, E. S., Babu, I. R. (2008). Authentication Using Fuzzy Vault Based on Iris Textures. 2008 Second Asia International Conference on Modelling & Simulation (AMS). doi: https://doi.org/10.1109/ams.2008.112

Prabhakar, S., Pankanti, S., Jain, A. K. (2003). Biometric recognition: security and privacy concerns. IEEE Security & Privacy, 1 (2), 33–42. doi: https://doi.org/10.1109/msecp.2003.1193209

Reddy, E. S., Babu, I. R. (2008). Performance of Iris Based Hard Fuzzy Vault. 2008 IEEE 8th International Conference on Computer and Information Technology Workshops. doi: https://doi.org/10.1109/cit.2008.workshops.20

Fouad, M., El Saddik, A., Zhao, J., Petriu, E. (2011). A fuzzy vault implementation for securing revocable iris templates. 2011 IEEE International Systems Conference. doi: https://doi.org/10.1109/syscon.2011.5929061

Nguyen, M. T., Truong, Q. H., Dang, T. K. (2016). Enhance fuzzy vault security using nonrandom chaff point generator. Information Processing Letters, 116 (1), 53–64. doi: https://doi.org/10.1016/j.ipl.2015.08.012

Lee, Y. J., Bae, K., Lee, S. J., Park, K. R., Kim, J. (2007). Biometric Key Binding: Fuzzy Vault Based on Iris Images. Lecture Notes in Computer Science, 800–808. doi: https://doi.org/10.1007/978-3-540-74549-5_84

Nandakumar, K., Jain, A. K. (2008). Multibiometric Template Security Using Fuzzy Vault. 2008 IEEE Second International Conference on Biometrics: Theory, Applications and Systems. doi: https://doi.org/10.1109/btas.2008.4699352

Geng, S., Giannopoulou, G., Kabir-Querrec, M. (2019). Privacy Protection in Distributed Fingerprint-based Authentication. Proceedings of the 18th ACM Workshop on Privacy in the Electronic Society - WPES’19. doi: https://doi.org/10.1145/3338498.3358648

Koptyra, K., Ogiela, M. R. (2018). Multiply information coding and hiding using fuzzy vault. Soft Computing, 23 (12), 4357–4366. doi: https://doi.org/10.1007/s00500-018-3089-x

Panwar, A., Singla, P., Kaur, M. (2017). Techniques for Enhancing the Security of Fuzzy Vault: A Review. Progress in Intelligent Computing Techniques: Theory, Practice, and Applications, 205–213. doi: https://doi.org/10.1007/978-981-10-3376-6_23

Rasool, R. A. (2018). Iris Feature Extraction and Recognition based on Gray Level Co-occurrence Matrix (GLCM) Technique. International Journal of Computer Applications, 181 (25), 15–17. doi: https://doi.org/10.5120/ijca2018917826

Hajari, K., Gawande, U., Golhar, Y. (2016). Neural Network Approach to Iris Recognition in Noisy Environment. Procedia Computer Science, 78, 675–682. doi: https://doi.org/10.1016/j.procs.2016.02.116

Rathgeb, C., Tams, B., Wagner, J., Busch, C. (2016). Unlinkable improved multi-biometric iris fuzzy vault. EURASIP Journal on Information Security, 2016 (1). doi: https://doi.org/10.1186/s13635-016-0049-9

Weerasinghe, T. D. B. (2012). Secrecy and Performance Analysis of Symmetric Key Encryption Algorithms. International Journal of Information and Network Security (IJINS), 1 (2). doi: https://doi.org/10.11591/ijins.v1i2.438

Singha, S., Sen, M. (2016). Encoding algorithm using bit level encryption and decryption technique. 2016 International Conference on Computer, Electrical & Communication Engineering (ICCECE). doi: https://doi.org/10.1109/iccece.2016.8009584

Chitra, D., Sujitha, V. (2019). Security analysis of prealigned fingerprint template using fuzzy vault scheme. Cluster Computing, 22 (S5), 12817–12825. doi: https://doi.org/10.1007/s10586-018-1762-6

Woodard, D. L., Ricanek, K. (2009). Iris Databases. Encyclopedia of Biometrics, 770–774. doi: https://doi.org/10.1007/978-0-387-73003-5_168

Kumar, A., Passi, A. (2010). Comparison and combination of iris matchers for reliable personal authentication. Pattern Recognition, 43 (3), 1016–1026. doi: https://doi.org/10.1016/j.patcog.2009.08.016

Uludag, U., Pankanti, S., Jain, A. K. (2005). Fuzzy Vault for Fingerprints. Audio- and Video-Based Biometric Person Authentication, 310–319. doi: https://doi.org/10.1007/11527923_32

Weik, M. H. (2000). Brute-Force Attack. Computer Science and Communications Dictionary, 149–149. doi: https://doi.org/10.1007/1-4020-0613-6_1898

Nandakumar, K., Jain, A. K., Pankanti, S. (2007). Fingerprint-Based Fuzzy Vault: Implementation and Performance. IEEE Transactions on Information Forensics and Security, 2 (4), 744–757. doi: https://doi.org/10.1109/tifs.2007.908165

Nagar, A., Nandakumar, K., Jain, A. K. (2010). A hybrid biometric cryptosystem for securing fingerprint minutiae templates. Pattern Recognition Letters, 31 (8), 733–741. doi: https://doi.org/10.1016/j.patrec.2009.07.003

Li, P., Yang, X., Cao, K., Tao, X., Wang, R., Tian, J. (2010). An alignment-free fingerprint cryptosystem based on fuzzy vault scheme. Journal of Network and Computer Applications, 33 (3), 207–220. doi: https://doi.org/10.1016/j.jnca.2009.12.003

Lee, Y. J., Park, K. R., Lee, S. J., Bae, K., Kim, J. (2008). A New Method for Generating an Invariant Iris Private Key Based on the Fuzzy Vault System. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 38 (5), 1302–1313. doi: https://doi.org/10.1109/tsmcb.2008.927261

Ahmed, H. M., Taha, M. A. (2021). A Brief Survey on Modern Iris Feature Extraction Methods. Engineering and Technology Journal, 39 (1A), 123–129. doi: https://doi.org/10.30684/etj.v39i1a.1680

Taha, M., Ahmed, H. (2021). Second-Order Statistical Methods GLCM for Authentication Systems. Iraqi Journal for Electrical and Electronic Engineering, 17 (1), 1–6. doi: https://doi.org/10.37917/ijeee.17.1.10

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How to Cite
Taha, M. A., & Ahmed, H. M. (2021). A fuzzy vault development based on iris images. EUREKA: Physics and Engineering, (5), 3-12. https://doi.org/10.21303/2461-4262.2021.001997
Computer Science