Protecting Movement Trajectories Through Fragmentation

Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 131)


Location-based applications (LBAs) like geo-social networks, points of interest finders, and real-time traffic monitoring applications have entered people’s daily life. Advanced LBAs rely on location services (LSs) managing movement trajectories of multiple users in a scalable fashion. However, exposing trajectory information raises user privacy concerns, in particular if LSs are non-trusted. For instance, an attacker compromising an LS can use the retrieved user trajectory for stalking, mugging, or to trace user movement. To limit the misuse of trajectory data, we present a new approach for the secure management of trajectories on non-trusted servers. Instead of providing the complete trajectory of a user to a single LS, we split up the trajectory into a set of fragments and distribute the fragments among LSs of different providers. By distributing fragments, we avoid a single point of failure in case of compromised LSs, while different LBAs can still reconstruct the trajectory based on user-defined access rights.

In our evaluation, we show the effectiveness of our approach by using real world trajectories and realistic attackers using map knowledge and statistical information to predict and reconstruct the user’s movement.


Location management Fragmentation Trajectories Privacy 


  1. 1.
    Ardagna, C., Livraga, G., Samarati, P.: Protecting privacy of user information in continuous location-based services. In: IEEE 15th International Conference on Computational Science and Engineering, pp. 162–169 (2012)Google Scholar
  2. 2.
    Beresford, A.R., Stajano, F.: Location privacy in pervasive computing. IEEE Pervasive Comput. 2(1), 46–55 (2003)CrossRefGoogle Scholar
  3. 3.
    Chow, C.-Y., Mokbel, M.F.: Enabling private continuous queries for revealed user locations. In: Papadias, D., Zhang, D., Kollios, G. (eds.) SSTD 2007. LNCS, vol. 4605, pp. 258–275. Springer, Heidelberg (2007) CrossRefGoogle Scholar
  4. 4.
    Damiani, M., Silvestri, C., Bertino, E.: Fine-grained cloaking of sensitive positions in location-sharing applications. Pervasive Comput. 10(4), 64–72 (2011)CrossRefGoogle Scholar
  5. 5.
    DATALOSSDB, June 2013.
  6. 6.
    Kalnis, P., Ghinita, G., Mouratidis, K., Papadias, D.: Preventing location-based identity inference in anonymous spatial queries. IEEE Trans. Knowl. Data Eng. 19(12), 1719–1733 (2007)CrossRefGoogle Scholar
  7. 7.
    Krumm, J.: A Markov model for driver turn prediction. In: Society of Automotive Engineers (SAE) World Congress (2008)Google Scholar
  8. 8.
    Nergiz, M.E., Atzori, M., Saygin, Y., Güç, B.: Towards trajectory anonymization: a generalization-based approach. Trans. Data Priv. 2(1), 47–75 (2009)MathSciNetGoogle Scholar
  9. 9.
    OpenStreetMap, June 2013.
  10. 10.
    Peddinti, S.T., Saxena, N.: On the limitations of query obfuscation techniques for location privacy. In: Proceedings of the 13th International Conference on Ubiquitous Computing (2011)Google Scholar
  11. 11.
    Piorkowski, M., Sarafijanovoc-Djukic, N., Grossglauser, M.: A parsimonious model of mobile partitioned networks with clustering. In: The First International Conference on COMmunication Systems and NETworkS, pp. 1–10 (2009)Google Scholar
  12. 12.
    Shankar, P., Ganapathy, V., Iftode, L.: Privately querying location-based services with sybilquery. In: Proceedings of the 11th International Conference on Ubiquitous Computing (2009)Google Scholar
  13. 13.
  14. 14.
    Wernke, M., Dürr, F., Rothermel, K.: PShare: ensuring location privacy in non-trusted systems through multi-secret sharing. Pervasive Mob. Comput. 9, 339–352 (2013)CrossRefGoogle Scholar
  15. 15.
    Wernke, M., Skvortsov, P., Dürr, F., Rothermel, K.: A classification of location privacy attacks and approaches. Pers. Ubiquit. Comput. 16, 1–13 (2012)CrossRefGoogle Scholar

Copyright information

© Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2014

Authors and Affiliations

  1. 1.Institute of Parallel and Distributed Systems (IPVS)University of StuttgartStuttgartGermany

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