An Improved Approach of Iris Biometric Authentication Performance and Security with Cryptography and Error Correction Codes

Sim Hiew Moi - Universiti Teknologi Malaysia, 81300 Skudai, Johor, Malaysia
Pang Yee Yong - Universiti Teknologi Malaysia, 81300 Skudai, Johor, Malaysia
Rohayanti Hassan - Universiti Teknologi Malaysia, 81300 Skudai, Johor, Malaysia
Hishammuddin Asmuni - Universiti Teknologi Malaysia, 81300 Skudai, Johor, Malaysia
Radziah Mohamad - Universiti Teknologi Malaysia, 81300 Skudai, Johor, Malaysia
Fong Cheng Weng - Tunku Abdul Rahman University College, Johor, Malaysia
Shahreen Kasim - Universiti Tun Hussein Onn Malaysia,, Johor, Malaysia

Citation Format:



One of the most challenging parts of integrating biometrics and cryptography is the intra variation in acquired identifiers between the same users. Due to noise in the environment or different devices, features of the iris may differ when it is acquired at different time periods. This research focuses on improving the performance of iris biometric authentication and encrypting the binary code generated from the acquired identifiers. The proposed biometric authentication system incorporates the concepts of non-repudiation and privacy. These concepts are critical to the success of a biometric authentication system. Iris was chosen as the biometric identifier due to its characteristics of high accuracy and the permanent presence throughout an individual’s lifetime. This study seeks to find a method of reducing the noise and error associated with the nature of dissimilarity acquired by each biometric acquisition.  In our method, we used Reed Solomon error-correction codes to reduce dissimilarities and noise in iris data. The code is a block-based error correcting code that can be easily decoded and has excellent burst correction capabilities. Two different distance metric measurement functions were used to measure the accuracy of the iris pattern matching identification process, which are Hamming distance and weighted Euclidean distance. The experiments were conducted with the CASIA 1.0 iris database. The results showed that the False Acceptance Rate is 0%, the False Rejection Rate is 1.54%, and the Total Success Rate is 98.46%. The proposed approach appears to be more secure, as it is able to provide a low rate of false rejections and false acceptances.


Biometric; iris; error correction codes; cryptography; encryption; decryption

Full Text:



M. Al Rousan, and B. Intrigila, “A Comparative Analysis of Biometrics Types: Literature Review,” Journal of Computer Science, vol. 16, no. 12, pp. 1778-1788, 2020.

T. Sabhanayagam, V. P. Venkatesan, and K. Senthamaraikannan, “A comprehensive survey on various biometric systems,” International Journal of Applied Engineering Research, vol. 13, no. 5, pp. 2276-2297, 2018.

C. Kuo, S. Romanosky, and L. F. Cranor, "Human selection of mnemonic phrase-based passwords." pp. 67-78.

B. Brumen, “Security analysis of Game Changer Password System,” International Journal of Human-Computer Studies, vol. 126, pp. 44-52, 2019/06/01/, 2019.

F. Hao, R. Anderson, and J. Daugman, “Combining crypto with biometrics effectively,” IEEE transactions on computers, vol. 55, no. 9, pp. 1081-1088, 2006.

T. C. Clancy, N. Kiyavash, and D. J. Lin, "Secure smartcardbased fingerprint authentication." pp. 45-52.

F. Monrose, M. K. Reiter, Q. Li, and S. Wetzel, "Cryptographic key generation from voice." pp. 202-213.

F. Monrose, M. K. Reiter, and S. Wetzel, “Password hardening based on keystroke dynamics,” International journal of Information security, vol. 1, no. 2, pp. 69-83, 2002.

A. K. Jain, A. Ross, and S. Prabhakar, “An introduction to biometric recognition,” IEEE Transactions on circuits and systems for video technology, vol. 14, no. 1, pp. 4-20, 2004.

M. L. Ali, J. V. Monaco, C. C. Tappert, and M. Qiu, “Keystroke Biometric Systems for User Authentication,” Journal of Signal Processing Systems, vol. 86, no. 2, pp. 175-190, 2017/03/01, 2017.

A. Jain, R. Bolle, and S. Pankanti, Biometrics: personal identification in networked society: Springer Science & Business Media, 1999.

A. Ahire, A. Jambhale, T. Patil, M. Chavan, A. Nerurkar, and R. V. Deolekar, "Comparative Analysis of Biometric Systems." pp. 895-901.

J. G. Daugman, “High confidence visual recognition of persons by a test of statistical independence,” IEEE transactions on pattern analysis and machine intelligence, vol. 15, no. 11, pp. 1148-1161, 1993.

J. L. Wayman, A. K. Jain, D. Maltoni, and D. Maio, Biometric systems: Technology, design and performance evaluation: Springer Science & Business Media, 2005.

J. Daugman, "Iris recognition," Handbook of biometrics, pp. 71-90: Springer, 2008.

R. P. Wildes, “Iris recognition: an emerging biometric technology,” Proceedings of the IEEE, vol. 85, no. 9, pp. 1348-1363, 1997.

S. Ziauddin, and M. N. Dailey, “Robust iris verification for key management,” Pattern Recognition Letters, vol. 31, no. 9, pp. 926-935, 2010.

I. S. Reed, and G. Solomon, “Polynomial codes over certain finite fields,” Journal of the society for industrial and applied mathematics, vol. 8, no. 2, pp. 300-304, 1960.

P. Ariyapreechakul, and N. Covavisaruch, “An improvement of iris pattern identification using radon transform,” ECTI Transactions on Computer and Information Technology (ECTI-CIT), vol. 3, no. 1, pp. 45-50, 2007.

R. P. Wildes, J. C. Asmuth, G. L. Green, S. C. Hsu, R. J. Kolczynski, J. R. Matey, and S. E. McBride, "A system for automated iris recognition." pp. 121-128.

C.-H. Chen, and C.-T. Chu, "Low complexity iris recognition based on wavelet probabilistic neural networks." pp. 1930-1935.

K. W. Bowyer, K. Hollingsworth, and P. J. Flynn, “Image understanding for iris biometrics: A survey,” Computer vision and image understanding, vol. 110, no. 2, pp. 281-307, 2008.

S. Yang, and I. Verbauwhede, "Secure iris verification." pp. II-133-II-136.

S. Kanade, D. Camara, E. Krichen, D. Petrovska-Delacrétaz, and B. Dorizzi, "Three factor scheme for biometric-based cryptographic key regeneration using iris." pp. 59-64.

X. Wu, N. Qi, K. Wang, and D. Zhang, "A novel cryptosystem based on iris key generation." pp. 53-56.

J. Bringer, H. Chabanne, G. Cohen, B. Kindarji, and G. Zémor, "Optimal iris fuzzy sketches." pp. 1-6.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

JOIV : International Journal on Informatics Visualization
ISSN 2549-9610  (print) | 2549-9904 (online)
Organized by Department of Information Technology - Politeknik Negeri Padang, and Institute of Visual Informatics - UKM and Soft Computing and Data Mining Centre - UTHM
W :
E :,,

View JOIV Stats

Creative Commons License is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.