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A Novel Fingerprint Biometric Cryptosystem Based on Convolutional Neural Networks

Author

Listed:
  • Srđan Barzut

    (Tehnikum Taurunum Department, Academy of Applied Technical Studies Belgrade, Nade Dimić 4, 11080 Belgrade, Serbia)

  • Milan Milosavljević

    (Faculty of Informatics and Computing, Singidunum University, Danijelova 32, 11000 Belgrade, Serbia)

  • Saša Adamović

    (Faculty of Informatics and Computing, Singidunum University, Danijelova 32, 11000 Belgrade, Serbia)

  • Muzafer Saračević

    (Department of Computer Sciences, University of Novi Pazar, Dimitrija Tucovića bb, 36300 Novi Pazar, Serbia)

  • Nemanja Maček

    (School of Electrical and Computer Engineering, Academy of Technical and Art Applied Studies, Vojvode Stepe 283, 11000 Belgrade, Serbia)

  • Milan Gnjatović

    (Department of Information Technology, University of Criminal Investigation and Police Studies, Cara Dušana 196, 11080 Belgrade, Serbia)

Abstract

Modern access controls employ biometrics as a means of authentication to a great extent. For example, biometrics is used as an authentication mechanism implemented on commercial devices such as smartphones and laptops. This paper presents a fingerprint biometric cryptosystem based on the fuzzy commitment scheme and convolutional neural networks. One of its main contributions is a novel approach to automatic discretization of fingerprint texture descriptors, entirely based on a convolutional neural network, and designed to generate fixed-length templates. By converting templates into the binary domain, we developed the biometric cryptosystem that can be used in key-release systems or as a template protection mechanism in fingerprint matching biometric systems. The problem of biometric data variability is marginalized by applying the secure block-level Bose–Chaudhuri–Hocquenghem error correction codes, resistant to statistical-based attacks. The evaluation shows significant performance gains when compared to other texture-based fingerprint matching and biometric cryptosystems.

Suggested Citation

  • Srđan Barzut & Milan Milosavljević & Saša Adamović & Muzafer Saračević & Nemanja Maček & Milan Gnjatović, 2021. "A Novel Fingerprint Biometric Cryptosystem Based on Convolutional Neural Networks," Mathematics, MDPI, vol. 9(7), pages 1-12, March.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:7:p:730-:d:525623
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