Abstract
Recently, with the extensive application of the location based services (LBS), more and more location privacy problems have happened. To use LBSs, users must send their location information to service provider, but users’ location information is private. The current methods have some flaws, such as in Euclidean space and so on. In this paper, a based historical user dummy generation (BHUDG) scheme is proposed, which can provide location privacy by utilizing density-based clustering method in a real road network environment. We investigate the effectiveness of BHUDG based on extensive simulation study. Simulation results show that our proposed scheme has a better performance.
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References
Meng, X., Pan, X.: Location based services privacy-preserving. CCCF 6(6), 16–22 (2010)
Kido, H., Yanagisawa, Y., Satoh, T.: Protection of location privacy using dummies for location-based services. In: Proc. of the 21st Int. Conf. on Data Engineering Workshops, pp. 1248–1248. IEEE, Washington (2005)
You, T., Peng, W., Lee, W.: Protecting moving trajectories with dummies. In: Proc. of 2007 Int. Conf. on Mobile Data Management, pp. 278–282. IEEE, Mannheim (2007)
Lu, H., Jensen, C.S., Yiu, M.L.: PAD: Privacy-Area Aware, Dummy-Based Location Privacy in Mobile Services. In: Proc. of Int. Workshop on Data Engineering for Wireless and Mobile Access, pp. 16–23. ACM, Canada (2008)
Suzuki, A., Iwata, M., Arase, Y., et al.: A user location anonymization method for location based services in a real environment. In: Proc. of the 18th SIGSPATIAL Int. Conf. on Advances in Geographic Information Systems, pp. 398–401. ACM, New York (2010)
Liu, H., Wang, T.J., Sun, M., et al.: Location privacy in sparse environment. In: Proc. of 2nd Int. Conf. on Advanced Computer Control (ICACC), pp. 258–261. IEEE, Shenyang China (2010)
Gruteser, M., Grunwald, D.: Anonymous usage of location-based services through spatial and temporal cloaking. In: Proc. of the 1st Int. Conf. on Mobile Systems, Applications, and Services (MOBISYS), pp. 31–42. ACM, New York (2003)
Zacharouli, P., Gkoulalas-Divanis, A., Verykios, V.S.: A k-anonymity model for spatio-temporal data. In: Proc. of the IEEE Workshop on Spatio-Temporal Data Mining (STDM), pp. 555–564. IEEE, Istanbul Turkey (2007)
Xu, T., Cai, Y.: Exploring historical location data for anonymity preservation in location-based services. In: Proc. of the 27th Conf. on Computer Communications, pp. 547–555. IEEE, Phoenix (2008)
Pan, X., Xiao, Z., Meng, X.: Survey of location privacy-preserving. Journal of Frontiers of Computer Science and Technology 1(3), 268–281 (2007)
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Han, Q., Zhao, H., Ma, Z., Zhang, K., Pan, H. (2014). Protecting Location Privacy Based on Historical Users over Road Networks. In: Cai, Z., Wang, C., Cheng, S., Wang, H., Gao, H. (eds) Wireless Algorithms, Systems, and Applications. WASA 2014. Lecture Notes in Computer Science, vol 8491. Springer, Cham. https://doi.org/10.1007/978-3-319-07782-6_32
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DOI: https://doi.org/10.1007/978-3-319-07782-6_32
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07781-9
Online ISBN: 978-3-319-07782-6
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