Abstract
It is very important for LBS popularization and application to study personalized location privacy preservation algorithms based on road networks for the mobile users. This paper proposes the Prediction Group by L algorithm (i.e., PL) in which the road networks is represented as a weighted graph, and the value of the weight of each edge is equal to its selection rate; the edges of the graph are sorted by the depth-first search algorithm, and grouped by the privacy degree of user where the group is used as the anonymous edge set (i.e., AES) to realize the location privacy preservation. The experimental results show that PL has high success rate of privacy. Additionally, it is able to provide higher quality personalized location privacy preservation because the AES generated by this algorithm is more approached to the privacy requirements of users than some other typical algorithms.
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Acknowledgments
This work was partially supported by the Natural Science Foundation of China (No. 61272403), by the Fundamental Research Funds for the Central Universities (No. 10561201474). We also appreciate Yaohui Zheng and Kai Tian for their kindly help of the experimental analysis and programming.
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Xu, H., Yang, J., Zhang, Y., Xu, M., Gan, J. (2015). Study on Personalized Location Privacy Preservation Algorithms Based on Road Networks. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9532. Springer, Cham. https://doi.org/10.1007/978-3-319-27161-3_4
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DOI: https://doi.org/10.1007/978-3-319-27161-3_4
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