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Achieving Privacy-Preserving Iris Identification Via El Gamal

Yong Ding1, Lei Tian1, Bo Han2, Huiyong Wang2,*, Yujue Wang1, James Xi Zheng3

Guangxi Key Laboratory of Cryptography and Information Security, School of Computer and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China.
School of Mathematics and Computer Science, Guilin University of Electronic Technology, Guilin, 541004, China.
Software Engineering Department of Computing, Macquarie University, Sydney, NSW 2109 Australia.

*Corresponding Author: Huiyong Wang. Email: email.

Computers, Materials & Continua 2019, 61(2), 727-738. https://doi.org/10.32604/cmc.2019.06220

Abstract

Currently, many biometric systems maintain the user’s biometrics and templates in plaintext format, which brings great privacy risk to uses’ biometric information. Biometrics are unique and almost unchangeable, which means it is a great concern for users on whether their biometric information would be leaked. To address this issue, this paper proposes a confidential comparison algorithm for iris feature vectors with masks, and develops a privacy-preserving iris verification scheme based on the El Gamal encryption scheme. In our scheme, the multiplicative homomorphism of encrypted features is used to compare of iris features and their mask information. Also, this paper improves the Hamming distance of iris features, which makes the similarity matching work better than existing ones. Experimental results confirm the practicality of our proposed schemes in real world applications, that is, for the iris feature vectors and masks of 2048 bits, nearly 12 comparisons can be performed per second.

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Cite This Article

Y. Ding, L. Tian, B. Han, H. Wang, Y. Wang et al., "Achieving privacy-preserving iris identification via el gamal," Computers, Materials & Continua, vol. 61, no.2, pp. 727–738, 2019. https://doi.org/10.32604/cmc.2019.06220

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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