An Irreversible and Revocable Template Generation Scheme Based on Chaotic System

Author:

Liu Jinyuan12ORCID,Wang Yong1,Wang Kun1,Liu Zhuo3

Affiliation:

1. College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

2. School of Intelligent Technology and Engineering, Chongqing University of Science and Technology, Chongqing 401331, China

3. School of Mathematics and Big Data, Guizhou Education University, Guiyang 550018, China

Abstract

Face recognition technology has developed rapidly in recent years, and a large number of applications based on face recognition have emerged. Because the template generated by the face recognition system stores the relevant information of facial biometrics, its security is attracting more and more attention. This paper proposes a secure template generation scheme based on a chaotic system. Firstly, the extracted face feature vector is permuted to eliminate the correlation within the vector. Then, the orthogonal matrix is used to transform the vector, and the state value of the vector is changed, while maintaining the original distance between the vectors. Finally, the cosine value of the included angle between the feature vector and different random vectors are calculated and converted into integers to generate the template. The chaotic system is used to drive the template generation process, which not only enhances the diversity of templates, but also has good revocability. In addition, the generated template is irreversible, and even if the template is leaked, it will not disclose the biometric information of users. Experimental results and theoretical analysis on the RaFD and Aberdeen datasets show that the proposed scheme has good verification performance and high security.

Funder

Doctoral Talent Training Project of Chongqing University of Posts and Telecommunications

Publisher

MDPI AG

Subject

General Physics and Astronomy

Reference38 articles.

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3. Cancelable Biometrics: A comprehensive survey;Manisha;Artif. Intell. Rev.,2020

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