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International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment

DIMVA 2016: Detection of Intrusions and Malware, and Vulnerability Assessment pp 377–396Cite as

Leveraging Sensor Fingerprinting for Mobile Device Authentication

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 9721))

Abstract

Device fingerprinting is a technique for identification and recognition of clients and widely used in practice for Web tracking and fraud prevention. While common systems depend on software attributes, sensor-based fingerprinting relies on hardware imperfections and thus opens up new possibilities for device authentication. Recent work focusses on accelerometers as easily accessible sensors of modern mobile devices. However, it has remained unclear if device recognition via sensor-based fingerprinting is feasible under real-world conditions.

In this paper, we analyze the effectiveness of a specialized feature set for sensor-based device fingerprinting and compare the results to feature-less fingerprinting techniques based on raw measurements. Furthermore, we evaluate other sensor types—like gravity and magnetic field sensors—as well as combinations of different sensors concerning their suitability for the purpose of device authentication. We demonstrate that combinations of different sensors yield precise device fingerprints when evaluating the approach on a real-world data set consisting of empirical measurement results obtained from almost 5,000 devices.

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Authors and Affiliations

  1. Horst Görtz Institute for IT-Security (HGI), Ruhr-Universität Bochum, Bochum, Germany

    Thomas Hupperich, Henry Hosseini & Thorsten Holz

Authors
  1. Thomas Hupperich
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  2. Henry Hosseini
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  3. Thorsten Holz
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Corresponding author

Correspondence to Thomas Hupperich .

Editor information

Editors and Affiliations

  1. IMDEA Software Institute, Pozuelo de Alarcón, Madrid, Spain

    Juan Caballero

  2. Mondragon University, Arrasate, Guipúzcoa, Spain

    Urko Zurutuza

  3. Universidad de Zaragoza, Zaragoza, Spain

    Ricardo J. Rodríguez

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© 2016 Springer International Publishing Switzerland

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Hupperich, T., Hosseini, H., Holz, T. (2016). Leveraging Sensor Fingerprinting for Mobile Device Authentication. In: Caballero, J., Zurutuza, U., Rodríguez, R. (eds) Detection of Intrusions and Malware, and Vulnerability Assessment. DIMVA 2016. Lecture Notes in Computer Science(), vol 9721. Springer, Cham. https://doi.org/10.1007/978-3-319-40667-1_19

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  • DOI: https://doi.org/10.1007/978-3-319-40667-1_19

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40666-4

  • Online ISBN: 978-3-319-40667-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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