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:



DOI: http://dx.doi.org/10.30630/joiv.6.2-2.1091

Abstract


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.

Keywords


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

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