Abstract
Location privacy receives considerable attentions in emerging location based services. Most current practice however fails to incorporate users’ preferences. In this paper, we propose a privacy protection solution to allow users’ preferences in the fundamental query of k nearest neighbors. Particularly, users are permitted to choose privacy preferences by specifying minimum inferred region. By leveraging Hilbert curve based transformation, the additional workload from users’ preferences is alleviated. What’s more, this transformation reduces time-expensive region queries in two dimensional space to range ones in one dimensional space. Therefore, the time efficiency, as well as communication efficiency, is greatly improved due to clustering properties of Hilbert curve. The empirical studies demonstrate our implementation delivers both flexibility for users’ preferences and scalability for time and communication costs.
This work is supported by the National Natural Science Foundation of China under grant No. 61003057 and No. 60973023.
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Ni, W., Zheng, J., Chong, Z., Lu, S., Hu, L. (2011). Location Privacy Protection in the Presence of Users’ Preferences. In: Wang, H., Li, S., Oyama, S., Hu, X., Qian, T. (eds) Web-Age Information Management. WAIM 2011. Lecture Notes in Computer Science, vol 6897. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23535-1_30
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DOI: https://doi.org/10.1007/978-3-642-23535-1_30
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