Similarity-based privacy protection for publishing k-anonymous trajectories

Shuai WANG, Chunyi CHEN, Guijie ZHANG

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Front. Comput. Sci. ›› 2022, Vol. 16 ›› Issue (3) : 163605. DOI: 10.1007/s11704-020-0271-y
Information Systems
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Similarity-based privacy protection for publishing k-anonymous trajectories

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Shuai WANG, Chunyi CHEN, Guijie ZHANG. Similarity-based privacy protection for publishing k-anonymous trajectories. Front. Comput. Sci., 2022, 16(3): 163605 https://doi.org/10.1007/s11704-020-0271-y

References

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Liu K , Yang J . Trajectory distance metric based on edit distance. Journal of Shanghai Jiaotong University, 2009, 43( 11): 50– 54
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Wang S , Chen C , Zhang G , Xin Y . Interchange-based privacy protection for publishing trajectories. IEEE Access, 2019, 7( 1): 138299– 138314
[3]
Abul O, Bonchi F, Nanni M. Never walk alone: uncertainty for anonymity in moving objects databases. In: Proceedings of IEEE International Conference on Data Engineering. 2008, 376-385
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Xin Y , Xie Z , Yang J . The privacy preserving method for dynamic trajectory releasing based on adaptive clustering. Information Sciences, 2017, 378 : 131– 143

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 61602133), Science and Technology Development Plan Project of Jilin Province (20180519012JH), and Scientific Items of Jilin Provincial Department of Education (JJKH20191025KJ).

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The supporting information is available online at journal.hep.com.cn and link.springer.com.

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