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Optimizing Placement of Mix Zones to Preserve Users’ Privacy for Continuous Query Services in Road Networks

  • Kamenyi Domenic M.
  • Yong Wang
  • Fengli Zhang
  • Yankson Gustav
  • Daniel Adu-Gyamfi
  • Nkatha Dorothy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8347)

Abstract

Location Based Services (LBS) are becoming very popular with today’s users. Some of these LBS require users to continuously send requests for services. This lead to leakages of both location and query contents to malicious adversaries. Further, if users are constrained by the nature of the road networks, an adversary can follow their path trajectory with ease. Most of the current privacy preserving solutions focus on temporal and spatial cloaking based methods to protect users’ location privacy. However, these solutions are vulnerable when subjected to continuous query environments. In this paper, we propose an optimized solution that preserves privacy for users’ trajectory for continuous LBS queries in road networks. First, we deploy a trusted third party architecture to provide anonymity for users as they use LBS services. Second, we utilize mix zone techniques and design two algorithms. The first algorithm, Abstraction Graph (AG), selects a sample of mix zones that satisfy the user desired privacy level under the acceptable service availability condition. The second algorithm, Optimized Decision Graph (ODG), utilizes the generated graph to find an optimal solution for the placement of mix zones through decomposition, chunking and replacement strategies. Finally, we analyze the capability of our algorithms to withstand attacks prone to mix zones and carry out experiments to verify this. The experiments results show that our Algorithms preserve privacy for users based on their privacy and service availability conditions.

Keywords

Location-based Services (LBSs) Privacy Preservation User Trajectory Continuous Query Decision Graphs 

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References

  1. 1.
    Chow, C.-Y., Mokbel, M.F.: Trajectory privacy in location-based services and data publication. ACM SIGKDD Explorations Newsletter (2011)Google Scholar
  2. 2.
    Chow, C.-Y., Mokbel, M.F., Bao, J., Liu, X.: Query-aware location anonymization for road networks. Geoinformatica (2011)Google Scholar
  3. 3.
    Freudiger, J., Shokri, R., Hubaux, J.-P.: On the optimal placement of mix zones. In: Goldberg, I., Atallah, M.J. (eds.) PETS 2009. LNCS, vol. 5672, pp. 216–234. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  4. 4.
    Al-Amin, H., Amina, H., Hye-Kyeom, Y., Jae-Woo, C.: H-star: Hilbert-order based star network expansion cloaking algorithm in road networks. In: 14th IEEE International Conference on Computational Science and Engineering, CSE (2011)Google Scholar
  5. 5.
    Jadliwala, M., Bilogrevic, I., Hubaux, J.-P.: Optimizing mix-zone coverage in pervasive wireless networks. In: JCS (2013)Google Scholar
  6. 6.
    Kotz, D., Henderson, T.: Crawdad, ncsu/mobilitymodels (2009), http://crawdad.cs.dartmouth.edu/meta.php?name=ncsu/
  7. 7.
    Xinxin, L., Han, Z., Miao, P., Hao, Y., Xiaolin, L., Yuguang, F.: Traffic-aware multi-mix-zone placement for protec. location priv. In: IEEE INFOCOM (2012)Google Scholar
  8. 8.
    Meyerowitz, J.T., Choudhury, R.R.: Realtime location privacy via mobility prediction: Creating confusion at crossroads. In: Proceedings of the 10th Workshop on Mobile Computing Systems and Applications (2009)Google Scholar
  9. 9.
    Wichian, P., Walisa, R., Nucharee, P.: Navigation without gps: Fake location for mobile phone tracking. In: 11th Intern. Conf. on ITS Telecomm. (2011)Google Scholar
  10. 10.
    Palanisamy, B., Liu, L., Lee, K., Singh, A., Tang, Y.: Location privacy with road network mix-zones. In: IEEE MSN (2012)Google Scholar
  11. 11.
    Palanisamy, B., Liu, L.: MobiMix. Protecting location privacy with mix-zones over road networks. In: IEEE 27th ICDE (2011)Google Scholar
  12. 12.
    Papoulis, A.: Prob., Random Processes and Stoch. Processes. Mc-Graw Hill (2003)Google Scholar
  13. 13.
    Pelikan, M.: Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms. STUDFUZZ, vol. 170. Springer, Heidelberg (2005)Google Scholar
  14. 14.
    Wang, T., Liu, L.: Privacy-aware mobile services over road networks. Proc. of Very Large Databases (VLDB) Endowment 2(1) (2009)Google Scholar
  15. 15.
    Yang, K.-T., Chiu, G.-M., Lyu, H.-J., Huang, D.-J., Teng, W.-C.: Path privacy protection in continuous location-based services over road networks. In: IEEE 8th International Conference on WiMob (2012)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Kamenyi Domenic M.
    • 1
  • Yong Wang
    • 1
  • Fengli Zhang
    • 1
  • Yankson Gustav
    • 1
  • Daniel Adu-Gyamfi
    • 1
  • Nkatha Dorothy
    • 1
  1. 1.School of Computer Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengduP.R. China

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