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Remote Biometrics for Robust Persistent Authentication

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Data Privacy Management and Autonomous Spontaneous Security (DPM 2013, SETOP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 8247))

Abstract

This paper examines the problem of providing a robust non-invasive authentication service for mobile users in a smart environment. We base our work on the persistent authentication model (PAISE), which relies on available sensors to track principals from the location where they authenticate, e.g., through a smart card based access control system, to the location where the authentication is required by a location-based service. The PAISE model is extended with remote biometrics to prevent the decay of authentication confidence when authenticated users encounter and interact with other users in the environment. The result is a calm approach to authentication, where mobile users are transparently authenticated towards the system, which allows the provision of location-based services. The output of the remote biometrics are fused using error-rate-based fusion to solve a common problem that occurs in score level fusion, i.e., the scores of each biometric system are usually incompatible, as they have different score ranges as well as different probability distributions.

We have integrated remote biometrics with the PAISE prototype and the experimental results on a publicly available dataset, show that fusion of two remote biometric modalities, facial recognition and appearance analysis, gives a significant improvement over each of the individual experts. Furthermore, the experimental results show that using remote biometrics increases the performance of tracking in persistent authentication, by identifying principals who are difficult to track due to occlusions in crowded scenes.

Christian D. Jensen—The research leading to these results has received funding from the [European Union] [European Atomic Energy Community] Seventh Framework Programme ([FP7/2007-2013] [FP7/2007-2011]) under grant agreement n [242497].

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Authors and Affiliations

  1. Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark

    Mads I. Ingwar & Christian D. Jensen

Authors
  1. Mads I. Ingwar
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  2. Christian D. Jensen
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Correspondence to Mads I. Ingwar .

Editor information

Editors and Affiliations

  1. TELECOM SudParis, Evry, France

    Joaquin Garcia-Alfaro

  2. National Technical University of Athens, Athens, Greece

    Georgios Lioudakis

  3. TELECOM Bretagne, Cesson Sévigné, France

    Nora Cuppens-Boulahia

  4. University College Cork, Cork, Ireland

    Simon Foley

  5. IDA Ovens, EMC Information Systems International, Cork, Ireland

    William M. Fitzgerald

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Ingwar, M.I., Jensen, C.D. (2014). Remote Biometrics for Robust Persistent Authentication. In: Garcia-Alfaro, J., Lioudakis, G., Cuppens-Boulahia, N., Foley, S., Fitzgerald, W. (eds) Data Privacy Management and Autonomous Spontaneous Security. DPM SETOP 2013 2013. Lecture Notes in Computer Science(), vol 8247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54568-9_16

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  • DOI: https://doi.org/10.1007/978-3-642-54568-9_16

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54567-2

  • Online ISBN: 978-3-642-54568-9

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