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Privacy for LBSs: On Using a Footprint Model to Face the Enemy

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Advanced Research in Data Privacy

Part of the book series: Studies in Computational Intelligence ((SCI,volume 567))

Abstract

User privacy in Location Based Services (LBSs) is still in need of effective solutions. A new privacy model for LBSs has been recently proposed based on users’ footprints—these being a representation of the amount of time a user spends in a given area. The model is claimed to be independent from the specific knowledge of the adversary about users’ footprints. Despite this claim, we show in this chapter that when the adversary has a knowledge that differs from the one considered for the anonymization procedure, the model is not valid. Further, we generalize this weakness of the model and show that it is highly probable that the footprint model provides: (i) either a privacy level lower than the expected one; or, (ii) a LBS information coarser than what would be required for anonymization purposes. We support our claim via analysis: modeling the footprints data as an hypercube model; with a simple example to grasp the main problem; and, with the study of a real data set of traces of mobile users. Finally, we also investigate which properties must hold for both the anonymiser and the adversary knowledge, in order to guarantee an effective level of user privacy.

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Notes

  1. 1.

    For instance, a German politician “discovered” his network operator collected 35,000 traces of his position in a period of 6 months. These data are now available to show the seriousness of the threat: http://www.zeit.de/datenschutz/malte-spitz-vorratsdaten.

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Acknowledgments

Mauro Conti is supported by a Marie Curie Fellowship funded by the European Commission under the agreement n. PCIG11-GA-2012-321980. This work has been partially supported by the TENACE PRIN Project 20103P34XC funded by the Italian MIUR.

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Authors and Affiliations

  1. University of Padua, Padua, Italy

    Mauro Conti

  2. University of Rome Tre, Rome, Italy

    Roberto Di Pietro

  3. Sapienza University of Rome, Rome, Italy

    Luciana Marconi

Authors
  1. Mauro Conti
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  2. Roberto Di Pietro
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  3. Luciana Marconi
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Corresponding author

Correspondence to Roberto Di Pietro .

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Editors and Affiliations

  1. Department of Information and Communications Engineering, Universitat Autonoma de Barcelona, Catalonia, Spain

    Guillermo Navarro-Arribas

  2. Consejo Superior de Investigaciones Científicas Campus de la UAB, Institut d'Investigació en Intel·ligència Artificial, Catalonia, Spain

    Vicenç Torra

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Conti, M., Pietro, R.D., Marconi, L. (2015). Privacy for LBSs: On Using a Footprint Model to Face the Enemy. In: Navarro-Arribas, G., Torra, V. (eds) Advanced Research in Data Privacy. Studies in Computational Intelligence, vol 567. Springer, Cham. https://doi.org/10.1007/978-3-319-09885-2_10

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  • DOI: https://doi.org/10.1007/978-3-319-09885-2_10

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  • Online ISBN: 978-3-319-09885-2

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