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Towards Location and Trajectory Privacy Protection in Participatory Sensing

  • Conference paper
Mobile Computing, Applications, and Services (MobiCASE 2011)

Abstract

The ubiquity of mobile devices has facilitated the prevalence of participatory sensing, whereby ordinary citizens using their private mobile devices to collect regional information and share with participators. However, such applications may endanger users’ privacy by revealing their locations and trajectories information. Most of existing solutions, which hide a user’s location information with a coarse region, are under k-anonymity model. Yet, they may not be applicable in some participatory sensing applications which require precise location information for high quality of service. In this paper, we present a method to protect the user’s location and trajectory privacy with high quality of service in some participatory sensing applications. Then, we utilize a new metric, called Slope Ratio (SR), to evaluate the method we proposed. The analysis and simulation results show that the method can protect the user’s location and trajectory privacy effectively.

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References

  1. Burke, J., Estrin, D., Hansen, M.: Participatory Sensing. In: Workshop on World Sensor Web: Mobile Device Centric Sensor Networks and Applications, USA, pp. 117–134 (2006)

    Google Scholar 

  2. Huang, K.L., Kanhere, S.S., Hu, W.: Preserving privacy in participatory sensing systems. Computer Communications 33, 1266–1280 (2010)

    Article  Google Scholar 

  3. Sweeney, L.: K-anonymity: A model for protecting privacy. International Journal Of Uncertainty Fuzziness And Knowledge Based Systems, 557–570 (2002)

    Google Scholar 

  4. Gruteser, M., Grunwald, D.: Anonymous usage of location-based service through spatial and temporal cloaking. In: Proceeding of the First International Conference on Mobile Systems, Applications, and Service, pp. 31–42 (2003)

    Google Scholar 

  5. Gedik, B., Liu, L.: Protecting Location Privacy with Personalized k-anonymity: Architecture and Algorithms. IEEE Transactions on Mobile Computing, 1–18 (2008)

    Google Scholar 

  6. Tang, M., Wu, Q.H., Zhang, G.P., He, L.L., Zhang, H.G.: A New Scheme of LBS Privacy Protection. In: Proceedings of the 5th International Conference on Wireless Communications, Networking and Mobile Computing, pp. 1–6 (2009)

    Google Scholar 

  7. Beresford, A.R., Stajano, F.: Location Privacy in Pervasive Computing. IEEE Pervasive Computing 2(1), 46–55 (2003)

    Article  Google Scholar 

  8. Beresford, A.R., Stajano, F.: Mix zones: User privacy in location-aware services. In: IEEE Workshop on Pervasive Computing and Communication Security, pp. 127–131 (2004)

    Google Scholar 

  9. Kapadia, A., Triandopoulos, N., Cornelius, C., Peebles, D., Kotz, D.: AnonySense: Opportunistic and privacy-preserving context collection. Computer Science (2008)

    Google Scholar 

  10. Kido, H., Yanagisawa, Y., Satoh, T.: An anonymous communication technique using dummies for location-based service. In: Proceedings of International Conference on Pervasive Service, pp. 88–97 (2005)

    Google Scholar 

  11. Dong, K., Gu, T., Tao, X.P., Lu, J.: Privacy protection in participatory sensing applications requiring fine-grained locations. In: 16th International Conference on Parallel and Distributed Systems, pp. 9–16 (2010)

    Google Scholar 

  12. You, T.H., Peng, W.C., Lee, W.C.: Protecting moving trajectories with dummies. In: 2007 International Conference on Mobile Data Management, pp. 278–282 (2007)

    Google Scholar 

  13. Gao, S., Ma, J., Shi, W., Zhan, G.: Technical Report MIST-TR-2011-101 (March 2011)

    Google Scholar 

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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Gao, S., Ma, J., Shi, W., Zhan, G. (2012). Towards Location and Trajectory Privacy Protection in Participatory Sensing. In: Zhang, J.Y., Wilkiewicz, J., Nahapetian, A. (eds) Mobile Computing, Applications, and Services. MobiCASE 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 95. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32320-1_29

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  • DOI: https://doi.org/10.1007/978-3-642-32320-1_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32319-5

  • Online ISBN: 978-3-642-32320-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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