Abstract
With the increase use of location-based services, location privacy has recently raised serious concerns. To protect a user from being identified, a cloaked spatial region that contains other k-1 nearest neighbors of the user is used to replace the accurate position. In this paper, we consider location-aware applications that services are different among regions. To search nearest neighbors, we define a novel distance measurement that combines the semantic distance and the Euclidean distance to address the privacy preserving issue in the above-mentioned applications. We also propose an algorithm kNNH to implement our proposed method. The experimental results further suggest that the proposed distance metric and the algorithm can successfully retain the utility of the location services while preserving users’ privacy.
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Zhang, L., Xiong, P., Zhu, T. (2014). Location Privacy Preserving for Semantic-Aware Applications. In: Batten, L., Li, G., Niu, W., Warren, M. (eds) Applications and Techniques in Information Security. ATIS 2014. Communications in Computer and Information Science, vol 490. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45670-5_13
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DOI: https://doi.org/10.1007/978-3-662-45670-5_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45669-9
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