Similarity-based privacy protection for publishing <i>k</i>-anonymous trajectories

doi:10.1007/s11704-020-0271-y

Front. Comput. Sci.

2022, Vol. 16

Issue (3) : 163605 https://doi.org/10.1007/s11704-020-0271-y

LETTER

Similarity-based privacy protection for publishing k-anonymous trajectories

Shuai WANG^1,², Chunyi CHEN¹(

), Guijie ZHANG³

¹. School of Computer Science and Technology, Changchun University of Science and Technology, Changchun 130022, China
². Teacher Training Center of Colleges and Universities of Jilin Province, Jilin Normal University, Siping 136000, China
³. School of Computer Science and Technology, Jilin Normal University, Siping 136000, China

Download: PDF(744 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Corresponding Author(s): Chunyi CHEN

Just Accepted Date: 18 September 2020 Issue Date: 18 September 2021

Cite this article:

Shuai WANG,Chunyi CHEN,Guijie ZHANG. Similarity-based privacy protection for publishing k-anonymous trajectories[J]. Front. Comput. Sci., 2022, 16(3): 163605.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-020-0271-y
https://academic.hep.com.cn/fcs/EN/Y2022/V16/I3/163605

Fig.1 The position relation of trajectories

Tab.1 Similarity between T ₁ and T ₂ to T ₆ ( α=1/2, β=1)

Fig.2 TRN of trajectories in Fig.1

1	K Liu , J Yang . Trajectory distance metric based on edit distance. Journal of Shanghai Jiaotong University, 2009, 43( 11): 50– 54
2	S Wang , C Chen , G Zhang , Y Xin . 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
4	Y Xin , Z Xie , J Yang . The privacy preserving method for dynamic trajectory releasing based on adaptive clustering. Information Sciences, 2017, 378 : 131– 143

[1]		Download
[2]		Download

Viewed

Full text

Abstract

Cited

Shared

Discussed