Abstract
Various mobile devices facilitate the users’ life, but the issues are brought into privacy focus by the individuals. This paper aims at the protection of intimate relationships among users. We consider the intimacy of user relationships based on similar sub-trajectories between the users. Then, we propose a \(k_{mn}\)-anonymity protection model. We generalize from two aspects: location and time. The first is location generalization. The range that user pass within the time that the location point stays is the generalization region, and the corresponding location point in the region’s trajectory is represented by the generalization region. When the location generalization is not enough to satisfy the \(k_{mn}\)-anonymity, then we use time generalization. Finally, the performance of our algorithm is evaluated by the experiment and the validity of our algorithm is verified.
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Acknowledgments
The research described in this paper was supported by the National Natural Science Foundation of China (U1401256), the National Natural Science Foundation of Liaoning province (201602094) and the Fundamental Research Funds for the Central Universities (3132018191).
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Yang, Z., Yang, M., Ning, B. (2020). User Relationship Privacy Protection on Trajectory Data. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 517. Springer, Singapore. https://doi.org/10.1007/978-981-13-6508-9_126
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DOI: https://doi.org/10.1007/978-981-13-6508-9_126
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