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Biometric Template Protection Using Deep Learning

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Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020) (SoCPaR 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1383))

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Abstract

Use of biometrics in digital society has raised the questions of biometric template protection and secure authentication. The biometric template protection mechanisms known so far hardly maintain a trade-off between security of template database and recognition performance. This paper proposes a hybrid technique of template protection for a multibiometric system that provides better matching performance and infallible from fraudulent attacks. The multimodal system is prepared from face and ECG biometrics. The ECG as a biometrics not only supplements the face biometrics in a multimodal system but also ensures security for robust recognition. The pre-trained deep learning models are used to process both biometrics and prepare multimodal templates. The templates are mapped to their corresponding classes represented by randomly generated unique binary codes. These binary codes are further encrypted using cryptographic hash for non-invertiblity and hide information of fused templates. Finally, the matching is performed using hash codes for ensuring an additional layer of defense against adversarial attacks.

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Author information

Authors and Affiliations

  1. Institute of Engineering and Technology, Dr APJ Abdul Kalam Technical University, Lucknow, 226021, Uttar Pradesh, India

    Ashutosh Singh & Yogendra Narain Singh

  2. National Informatics Centre, Ministry of Electronics and Information Technology, New Delhi, 110011, India

    Pramod Kumar

Authors
  1. Ashutosh Singh
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  2. Yogendra Narain Singh
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  3. Pramod Kumar
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Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Systems Innovation, School of Engineering, The University of Tokyo, Bunkyo-ku, Tokyo, Japan

    Yukio Ohsawa

  3. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  4. Vardhaman College of Engineering, Hyderabad, Telangana, India

    M.A. Jabbar

  5. Faculty of Sciences and Techniques, Hassan 1st University, Settat, Morocco

    Abdelkrim Haqiq

  6. Queen’s University, Belfast, UK

    Seán McLoone

  7. Northumbria University, Newcastle, UK

    Biju Issac

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Singh, A., Singh, Y.N., Kumar, P. (2021). Biometric Template Protection Using Deep Learning. In: Abraham, A., et al. Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020). SoCPaR 2020. Advances in Intelligent Systems and Computing, vol 1383. Springer, Cham. https://doi.org/10.1007/978-3-030-73689-7_91

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