Realistic Driving Trips For Location Privacy

  • John Krumm
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5538)

Abstract

Simulated, false location reports can be an effective way to confuse a privacy attacker. When a mobile user must transmit his or her location to a central server, these location reports can be accompanied by false reports that, ideally, cannot be distinguished from the true one. The realism of the false reports is important, because otherwise an attacker could filter out all but the real data. Using our database of GPS tracks from over 250 volunteer drivers, we developed probabilistic models of driving behavior and applied the models to create realistic driving trips. The simulations model realistic start and end points, slightly non-optimal routes, realistic driving speeds, and spatially varying GPS noise.

Keywords

location privacy location-based services false trips GPS 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Duckham, M., Kulik, L.: A Formal Model of Obfuscation and Negotiation for Location Privacy. In: Gellersen, H.-W., Want, R., Schmidt, A. (eds.) Pervasive 2005. LNCS, vol. 3468, pp. 152–170. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  2. 2.
    Duckham, M., Kulik, L., Birtley, A.: A Spatiotemporal Model of Strategies and Counter Strategies for Location Privacy Protection. In: Raubal, M., Miller, H.J., Frank, A.U., Goodchild, M.F. (eds.) GIScience 2006. LNCS, vol. 4197, pp. 47–64. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  3. 3.
    Gruteser, M., Grunwald, D.: Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking. In: First ACM/USENIX International Conference on Mobile Systems, Applications, and Services (MobiSys 2003), pp. 31–42. ACM Press, San Francisco (2003)CrossRefGoogle Scholar
  4. 4.
    Gruteser, M., Hoh, B.: On the Anonymity of Periodic Location Samples. In: Hutter, D., Ullmann, M. (eds.) SPC 2005. LNCS, vol. 3450, pp. 179–192. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  5. 5.
    Harri, J., Filali, F., Bonnet, C.: Mobility Models for Vehicular Ad Hoc Networks: A Survey and Taxonomy, Institut Eurecom, Department of Mobile Communications: Sophia-Antipolis, FRANCE (2007)Google Scholar
  6. 6.
    Hoh, B., et al.: Enhancing Security and Privacy in Traffic-Monitoring Systems. In: IEEE Pervasive Computing Magazine, pp. 38–46. IEEE, Los Alamitos (2006)Google Scholar
  7. 7.
  8. 8.
    Hu, P.S., Reuscher, T.R.: Summary of Travel Trends, National Household Travel Survey, U. S. Department of Transportation, U.S. Federal Highway Administration. p. 135 (2001)Google Scholar
  9. 9.
    Kido, H., Yanagisawa, Y., Satoh, T.: An Anonymous Communication Technique Using Dummies For Location-based Services. In: IEEE International Conference on Pervasive Services 2005 (ICPS 2005), Santorini, Greece, pp. 88–97 (2005)Google Scholar
  10. 10.
    Krumm, J.: Inference Attacks on Location Tracks. In: LaMarca, A., Langheinrich, M., Truong, K.N. (eds.) Pervasive 2007. LNCS, vol. 4480, pp. 127–143. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  11. 11.
    Krumm, J., Letchner, J., Horvitz, E.: Map Matching with Travel Time Constraints. In: Society of Automotive Engineers (SAE) 2007 World Congress, Detroit, MI USA (2007)Google Scholar
  12. 12.
    Letchner, J., Krumm, J., Horvitz, E.: Trip Router with Individualized Preferences (TRIP): Incorporating Personalization into Route Planning. In: Eighteenth Conference on Innovative Applications of Artificial Intelligence (IAAI 2006), Boston, Massachusetts USA (2006)Google Scholar
  13. 13.
    Rish, I.: An Empirical Study of the Naive Bayes Classifier. In: IJCAI 2001 Workshop on Empirical Methods in AI (2001)Google Scholar
  14. 14.
    Rousseeuw, P.J., Croux, C.: Alternatives to the Median Absolute Deviation. Journal of the Americal Statistical Association 88(424), 1273–1283 (1993)MathSciNetCrossRefMATHGoogle Scholar
  15. 15.
    Steffen, M.: A Simple Method for Monotonic Interpolation in One Dimension. Astronomy and Astrophysics 239(II), 443–450 (1990)Google Scholar
  16. 16.
    van Diggelen, F.: GNSS Accuracy: Lies, Damn Lies, and Statistics. In: GPS World (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • John Krumm
    • 1
  1. 1.Microsoft Research, Microsoft Corporation, One Microsoft WayRedmondUSA

Personalised recommendations