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Roadmap for Privacy Protection in Mobile Sensing Applications

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Abstract

Current mobile phones feature a continuously increasing number of embedded sensors. This opens the doors to a wide range of novel mobile sensing applications, which can potentially benefit from sensor readings collected by billions of mobile phone subscribers. The collection of fine-grained sensor readings can however endanger multiple aspects of the privacy of the users contributing to these applications by, e.g., revealing their whereabouts or the social relationships. In this manuscript, we identify potential threats to privacy by considering each collected sensor modality individually. We then present selected privacy-preserving mechanisms specially tailored for mobile sensing applications and identify future research directions to further enhance the privacy protection of users contributing to such applications.

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Notes

  1. 1.

    Prashanth Mohan, Venkata N. Padmanabhan, and Ramachandran Ramjee, “Nericell: Rich Monitoring of Road and Traffic Conditions Using Mobile Smartphones,” in Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems (SenSys), 2008.

  2. 2.

    Rajib K. Rana et al., “Ear-Phone: An End-to-end Participatory Urban Noise Mapping System,” in Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), 2010.

  3. 3.

    Katie Shilton, “Four Billion Little Brothers?: Privacy, Mobile Phones, and Ubiquitous Data Collection,” Communications of the ACM 52 (2009).

  4. 4.

    “Sun SPOT Main Board Technical Datasheet,” http://www.sunspotworld.com (accessed in 02.2012).

  5. 5.

    “TelosB Datasheet,” http://www.memsic.com (accessed in 02.2012).

  6. 6.

    Delphine Christin and Matthias Hollick, “We Must Move – We Will Move: On Mobile Phones as Sensing Platforms,” in Proceedings of the 10th GI/ITG KuVS Fachgespräch Drahtlose Sensornetze (FGSN), 2011.

  7. 7.

    “iPhone 4S Technical Specifications,” http://www.apple.com (accessed in 02.2012).

  8. 8.

    “Global GSM and 3GSM Mobile Connections,” http://www.gsm.com (accessed in 02.2012).

  9. 9.

    Yi F. Dong et al., “Automatic Collection of Fuel Prices from a Network of Mobile Cameras,” in Proceedings of the 4th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS), 2008.

  10. 10.

    Min Mun et al., “PEIR, the Personal Environmental Impact Report, as a Platform for Participatory Sensing Systems Research,” in Proceedings of the 7th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys), 2009.

  11. 11.

    Shane B. Eisenman et al., “BikeNet: A Mobile Sensing System for Cyclist Experience Mapping,” ACM Transactions on Sensor Networks 6 (2009).

  12. 12.

    Shilton, “Four Billion Little Brothers?”.

  13. 13.

    Mohan, “Nericell”.

  14. 14.

    Rana, “Ear-Phone”.

  15. 15.

    Eiman Kanjo et al., “MobSens: Making Smart Phones Smarter,” IEEE Pervasive Computing 8 (2009).

  16. 16.

    Nicolas Maisonneuve et al., “NoiseTube: Measuring and Mapping Noise Pollution with Mobile Phones,” in Proceedings of the 4th International Symposium on Information Technologies in Environmental Engineering (ITEE), 2009.

  17. 17.

    Delphine Christin et al., A Survey on Privacy in Mobile Participatory Sensing Applications, Journal of Systems & Software 84 (2011).

  18. 18.

    Christin, A Survey on Privacy in Mobile Participatory Sensing Applications.

  19. 19.

    Anthony LaMarca et al., “Place Lab: Device Positioning Using Radio Beacons in the Wild,” Pervasive Computing 3468 (2005).

  20. 20.

    Shilton, “Four Billion Little Brothers?”.

  21. 21.

    Ling Liu, “From Data Privacy to Location Privacy: Models and Algorithms,” in Proceedings of the 33rd International Conference on Very Large Data Bases (VLBD), 2007.

  22. 22.

    John Krumm, “Inference Attacks on Location Tracks,” in Proceedings of the 5th IEEE International Conference on Pervasive Computing (Pervasive), 2007.

  23. 23.

    Rana, “Ear-Phone”.

  24. 24.

    Christin, A Survey on Privacy in Mobile Participatory Sensing Applications.

  25. 25.

    Ibid.

  26. 26.

    Mohan, “Nericell”.

  27. 27.

    Mohammad O. Derawi et al., “Unobtrusive User-authentication on Mobile Phones using Biometric Gait,” in Proceeding of the 6th IEEE International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2010.

  28. 28.

    Philip Marquardt et al., “(sp)iPhone: Decoding Vibrations from Nearby Keyboards using Mobile Phone Accelerometers,” in Proceedings of the 18th ACM Conference on Computer and Communications Security (CCS), 2011.

  29. 29.

    Rana, “Ear-Phone”.

  30. 30.

    Bret Hull et al., “CarTel: A Distributed Mobile Sensor Computing System,” in Proceedings of the 4th ACM International Conference on Embedded Networked Sensor Systems (SenSys), 2006.

  31. 31.

    Krumm, “Inference Attacks on Location Tracks”.

  32. 32.

    Katie Shilton et al., “Participatory Privacy in Urban Sensing,” in Proceedings of the International Workshop on Mobile Devices and Urban Sensing (MODUS), 2008.

  33. 33.

    Tathagata Das et al., “PRISM: Platform for Remote Sensing using Smartphones,” in Proceedings of the 8th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys), 2010.

  34. 34.

    Shilton, “Participatory Privacy in Urban Sensing”.

  35. 35.

    Mun, “PEIR”.

  36. 36.

    Ramón Cáceres et al., “Virtual Individual Servers as Privacy-Preserving Proxies for Mobile Devices,” in Proceedings of the 1st ACM Workshop on Networking, Systems, and Applications for Mobile Handhelds (MobiHeld), 2009.

  37. 37.

    Rana, “Ear-Phone”.

  38. 38.

    Emiliano Miluzzo et al., “Sensing Meets Mobile Social Networks: The Design, Implementation and Evaluation of the CenceMe Application,” in Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems (SenSys), 2008.

  39. 39.

    Raghu K. Ganti et al., “PoolView: Stream Privacy for Grassroots Participatory Sensing,” in Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems (SenSys), 2008.

  40. 40.

    Latanya Sweeney, “K-Anonymity: A Model for Protecting Privacy,” International Journal of Uncertainty, Fuzziness, and Knowledge-Based Systems 10 (2002).

  41. 41.

    Minho Shin et al., “AnonySense: A System for Anonymous Opportunistic Sensing,” Journal of Pervasive and Mobile Computing 7 (2010).

  42. 42.

    Kuan L. Huang, Salil S. Kanhere, and Wen Hu, “Preserving Privacy in Participatory Sensing Systems,” Computer Communications 33 (2010).

  43. 43.

    Josep Domingo-Ferrer and Josep M. Mateo-Sanz, “Practical Data-Oriented Microaggregation for Statistical Disclosure Control,” IEEE Transactions on Knowledge and Data Engineering 14 (2002).

  44. 44.

    Christin, A Survey on Privacy in Mobile Participatory Sensing Applications.

  45. 45.

    Ibid.

  46. 46.

    Marc Langheinrich, “Personal Privacy in Ubiquitous Computing – Tools and System Support” (Ph.D. diss., ETH Zurich, 2005).

  47. 47.

    Delphine Christin et al., “Privacy-Preserving Collaborative Path Hiding for Participatory Sensing Applications,” in Proceedings of the 8th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS), 2011.

  48. 48.

    Das, “PRISM”.

  49. 49.

    Anne Adams and Martina A. Sasse, “Users Are Not the Enemy”. Communications of the ACM 42 (1999).

  50. 50.

    Alma Whitten and J. D. Tygar, “Why Johnny Can’t Encrypt: A Usability Evaluation of PGP 5.0,” in Proceedings of the USENIX Security Symposium (SSYM), 1999.

  51. 51.

    Lothar Fritsch, “Profiling and Locations-Based Services”, in Profiling the European Citizen – Cross-Disciplinary Perspective, ed. Mireille Hildebrandt and Serge Gutwirth (Dordrecht: Springer Netherlands), 2008.

  52. 52.

    Jan Zibuschka et al., “Enabling Privacy of Real-Life LBS: A Platform for Flexible Mobile Service Provisioning,” in Proceedings of the 22nd IFIP TC-11 International Information Security Conference, 2007.

  53. 53.

    Ming-Chi Lee, “Factors Influencing the Adoption of Internet Banking: An Integration of TAM and TPB with Perceived Risk and Perceived Benefit,” Electronic Commerce Research and Applications 8 (2009).

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Authors and Affiliations

  1. Secure Mobile Networking Lab, Center for Advanced Security Research Darmstadt (CASED), Technische Universität Darmstadt, Mornewegstr. 32, 64293, Darmstadt, Germany

    Delphine Christin & Matthias Hollick

Authors
  1. Delphine Christin
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  2. Matthias Hollick
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Correspondence to Delphine Christin .

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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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Christin, D., Hollick, M. (2013). Roadmap for Privacy Protection in Mobile Sensing Applications. 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_9

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