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A biometric cryptosystem scheme based on random projection and neural network

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A Correction to this article was published on 19 April 2021

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Abstract

Several biometric cryptosystem techniques have been proposed to protect biometric templates and preserve users’ privacy. Although such techniques can thwart different attacks, it is difficult to achieve well non-linkability between biometric cryptosystems. In this paper, we propose a novel biometric cryptosystem scheme based on random projection (RP) and back propagation neural network (BPNN) to perform the task of biometric template protection. With the help of RP, an original biometric feature vector can be projected onto a fix-length feature vector of random subspace that is derived from a user-specific projection matrix. This process is revocable and produces unlinkable biometric templates. The proposed scheme further utilizes a BPNN model to bind a projected feature vector with a random key. Based on BPNN, a robust mapping between a projected feature vector and a random key is learned to generate an error-correction-based biometric cryptosystem. The security of the proposed scheme is analyzed and the experimental results on multiple biometric datasets show the feasibility and efficiency of the proposed scheme.

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Acknowledgements

This work is supported by the 2019-“Chunhui Plan” Cooperative Scientific Research Project of Ministry of Education of China (Grant No. HLJ2019015), Heilongjiang Provincial Natural Science Foundation of China (Grant No. LH2020F044), the Fundamental Research Funds for Heilongjiang Universities, China (Grant No. 2020-KYYWF-1014), and the Guangxi Key Laboratory of Cryptography and Information Security (GCIS201904).

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Authors and Affiliations

  1. School of Data Science and Technology, Heilongjiang University, Harbin, China

    Jialiang Peng

  2. Guangxi Key Laboratory of Cryptography and Information Security, Guilin, China

    Jialiang Peng

  3. Department of Information Security and Communication Technology, Norwegian University of Science and Technology, Gjøvik, Norway

    Bian Yang

  4. Computer Engineering Department, NIT Kurukshetra, Kurukshetra, India

    B. B. Gupta

  5. Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan

    B. B. Gupta

  6. Department of Mathematics and Computer Science, Faculty of Science, Menoufia University, Shebin El-Koom, Egypt

    Ahmed A. Abd El-Latif

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  1. Jialiang Peng
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  2. Bian Yang
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  3. B. B. Gupta
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  4. Ahmed A. Abd El-Latif
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Corresponding authors

Correspondence to Jialiang Peng or B. B. Gupta.

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We declare that no conflict of interest exits in the submission of this manuscript. All the procedures performed in this study were in accordance with the ethical standards. We further declare that informed consent was obtained from all individual participants included in the study.

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Peng, J., Yang, B., Gupta, B.B. et al. A biometric cryptosystem scheme based on random projection and neural network. Soft Comput 25, 7657–7670 (2021). https://doi.org/10.1007/s00500-021-05732-2

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