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Privacy Preserving Multimodal Biometric Authentication in the Cloud

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Green, Pervasive, and Cloud Computing (GPC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10232))

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Abstract

In this paper, we describe the first privacy preserving multimodal biometric authentication protocol resistant to hill climbing attacks. Due to the encrypted storage and processing in the encrypted domain, the biometric database can be outsourced to the cloud. Our scheme is based on the combination of two different cryptographic primitives operating on encrypted biometric templates generated either from a single trait such as fingerprint or multimodal biometrics. For the former, the scheme employs multiple matchers working on set overlap and euclidean distance resulting in two different matching scores. In both cases, quantized scores are combined privately, to prevent any party accessing the final fused matching score. This way, hill climbing attacks are prevented that are applicable even if the templates are stored as encrypted. Finally, the scheme benefits from the advantages of multimodal biometrics and the efficiency of the underlying primitives with linear computation and communication overhead.

Dr. N. Deniz Sarier is an external researcher in Bonn-Aachen International Center for Information Technology (B-IT), Computer Security Group (cosec).

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Acknowledgement

The author is grateful to Prof. Dr. Joachim von zur Gathen for his valuable support, encouragement and guidance.

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Authors and Affiliations

  1. B-IT, cosec, Dahlmannstr. 2, 53113, Bonn, Germany

    Neyire Deniz Sarier

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  1. Neyire Deniz Sarier
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Correspondence to Neyire Deniz Sarier .

Editor information

Editors and Affiliations

  1. Hong Kong Polytechnic University, Hong Kong, Hong Kong

    Man Ho Allen Au

  2. University of Salerno, Fisciano, Italy

    Arcangelo Castiglione

  3. University of Texas at San Antonio, San Antonio, Texas, USA

    Kim-Kwang Raymond Choo

  4. University of Salerno, Fisciano, Italy

    Francesco Palmieri

  5. Providence University, Taichung City, Taiwan

    Kuan-Ching Li

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Sarier, N.D. (2017). Privacy Preserving Multimodal Biometric Authentication in the Cloud. In: Au, M., Castiglione, A., Choo, KK., Palmieri, F., Li, KC. (eds) Green, Pervasive, and Cloud Computing. GPC 2017. Lecture Notes in Computer Science(), vol 10232. Springer, Cham. https://doi.org/10.1007/978-3-319-57186-7_8

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  • DOI: https://doi.org/10.1007/978-3-319-57186-7_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57185-0

  • Online ISBN: 978-3-319-57186-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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