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Privacy Enhancing Techniques for the Protection of Mobility Patterns in LBS: Research Issues and Trends

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European Data Protection: Coming of Age

Abstract

LBS have become an integral part of users’ experiences, delivering users targeted, relevant and highly convenient information. However, the significant advantages associated with LBS come at a price to users’ privacy. While the location of a mobile device at any given moment may not be particularly sensitive, the historical trail of past locations, i.e. the users’ trajectories, can reveal much about a user’s behavior. Over the past few years there has been a flourishing of research initiatives specifically addressing the development of techniques for the safeguard of the position information in LBS (Position PETs). In this paper we analyze pros and cons of major research streams. We also discuss some emerging trends in LBS which are valuable for their implications on privacy and future research in the field. The ultimate goal is to foster cross-disciplinary discussion on the requirements and limits of Position PETs in the light of emerging privacy demands and on-going research.

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Notes

  1. 1.

    Ericsson. Traffic market and data report. Nov. 2011.

  2. 2.

    John Krumm. “A Survey of Computational Location Privacy” 2009.

  3. 3.

    Christian Jensen et al. “Location Privacy Techniques in Client-Server Architectures”. 2009.

  4. 4.

    Pankaj Mehra. “Context-Aware Computing: Beyond Search and Location-Based Services”. 2012.

  5. 5.

    Giovanni Iachello et al. “End-User Privacy in Human-Computer Interaction”. 2007.

  6. 6.

    Security Steering Committee on the Usability and Privacy of Computer Systems; National Research Council. “Overview of Security, Privacy, and Usability”. 2010.

  7. 7.

    http://www.google.com/latitude.

  8. 8.

    Fosca Giannotti et al. “Trajectory Pattern Mining”. 2007.

  9. 9.

    Xin Cao et al. “Mining Significant Semantic Locations from GPS Data”. 2010.

  10. 10.

    Stefano Spaccapietra et al. “A Conceptual View on Trajectories”. 2008.

  11. 11.

    Byoungyoung Lee et al. “Protecting Location Privacy Using Location Semantics”. 2011.

  12. 12.

    Article29 Data Protection Working Party. Opinion 13/2011. 2011.

  13. 13.

    Mark Gruteser et al. “Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking”. 2003.

  14. 14.

    Alastair Beresford et al. “Location Privacy in Pervasive Computing”. 2003.

  15. 15.

    Christian Jensen et al. “Location Privacy Techniques in Client-Server Architectures”. 2009.

  16. 16.

    Reza Shokri et al. “Quantifying Location Privacy”. 2011.

  17. 17.

    IETF. “An Architecture for Location and Location Privacy in Internet Application”. 2011.

  18. 18.

    Lorrie Cranor. “P3P: Making Privacy Policies More Useful”. 2003.

  19. 19.

    Eran Toch et al. “Locaccino: A Privacy Centric Location Sharing Appplication”. 2010.

  20. 20.

    Tsai, Janice et al. “Who’s Viewed You?: The Impact of Feedback in a Mobile Location-Sharing Application”. 2009.

  21. 21.

    Mark Gruteser et al. “Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking”. 2003.

  22. 22.

    Chi-Yin. Chow et al. “Trajectory Privacy in Location-Based Services and Data Publication”. 2011.

  23. 23.

    Mohamed Mokbel et al. “The New Casper: Query Processing for Location Services Without Compromising Privacy”. 2006.

  24. 24.

    Gabriel Ghinita et al. “MobiHide: A Mobile Peer-to-Peer System for Anonymous Location-Based Queries”. 2007.

  25. 25.

    Mark Gruteser et al., 2003, see note 19.

  26. 26.

    Carmen Ruiz Vicente et al. “Location-Related Privacy in Geo-Social Networks”. 2011.

  27. 27.

    Man Lung Yiu et al. “SpaceTwist: Managing the Trade-Offs Among Location Privacy, Query Performance, and Query Accuracy in Mobile Services”. 2008.

  28. 28.

    IETF, 2011, see note 16.

  29. 29.

    http://fireeagle.yahoo.net/.

  30. 30.

    Claudio Ardagna et al. “Location Privacy Protection Through Obfuscation-Based Techniques”. 2006.

  31. 31.

    Marc Duckham et al. “A Formal Model of Obfuscation and Negotiation for Location Privacy”. 2005.

  32. 32.

    Reynold Cheng et al. “Preserving User Location Privacy in Mobile Data Management Infrastructures”. 2006.

  33. 33.

    Gabriel Ghinita et al. “Private Queries in Location Based Services: Anonymizers Are Not Necessary”. 2008.

  34. 34.

    Gabriel Ghinita et al. “Preventing Velocity-Based Linkage Attacks in Location-Aware Applications”. 2009.

  35. 35.

    Byoungyoung Lee et al. “Protecting Location Privacy Using Location Semantics”. 2011.

  36. 36.

    Maria Luisa Damiani et al. “Fine-Grained Cloaking of Sensitive Positions in Location Sharing Applications”. 2011.

  37. 37.

    See note 36.

  38. 38.

    Maria Luisa Damiani et al. “The PROBE Frame Work for the Protection of Sensitive Positions”. 2010.

  39. 39.

    Emre Yigitoglu et al. “Privacy-Preserving Sharing of Sensitive Semantic Locations Under Road Constraints”. 2012.

  40. 40.

    Maria Luisa Damiani. “Third Party Geo-Location Services: Privacy Requirements and Research Issues”. 2011.

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Authors and Affiliations

  1. Department of Computer Science, University of Milan, 39, Via Comelico, Milan, 20135, Italy

    Maria Luisa Damiani

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  1. Maria Luisa Damiani
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Correspondence to Maria Luisa Damiani .

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Editors and Affiliations

  1. Pleinlaan 2, Brussel, 1050, Belgium

    Serge Gutwirth

  2. , TILT, Tilburg University, Warandelaan 2, Tilburg, 5037 AB, Netherlands

    Ronald Leenes

  3. , LSTS, Vrije Universiteit Brussel, Avenue de la Plaine 2, Brussels, 1050, Belgium

    Paul de Hert

  4. Research Centre for Information, Technology & Law, University of Namur, Rempart de la Vierge 5, Namur, 5000, Belgium

    Yves Poullet

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Damiani, M.L. (2013). Privacy Enhancing Techniques for the Protection of Mobility Patterns in LBS: Research Issues and Trends. In: Gutwirth, S., Leenes, R., de Hert, P., Poullet, Y. (eds) European Data Protection: Coming of Age. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5170-5_10

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