A User Study on the Capability of Three Geo-Based Features in Analyzing and Locating Trajectories

Visual analysis is widely applied to study human mobility due to the ability of integrating contextual information from multiple data sources. Analyzing trajectory data through visualization improves the efficiency and accuracy of the analysis, yet it may induce exposure of the location privacy. To...

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Bibliographic Details
Published inIEEE transactions on intelligent transportation systems Vol. 20; no. 9; pp. 3375 - 3385
Main Authors Wang, Xumeng, Gu, Tianlong, Luo, Xiaonan, Cai, Xiwen, Lao, Tianyi, Chen, Wenlong, Wu, Yingcai, Yu, Jinhui, Chen, Wei
Format Journal Article
LanguageEnglish
Published New York IEEE 01.09.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Correlation
Data analysis
Data privacy
evaluation
geo-based context
location privacy
Periodic trajectory
Privacy
Roads
Surveying
Task analysis
Trajectory
Trajectory analysis
Visualization
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Summary:Visual analysis is widely applied to study human mobility due to the ability of integrating contextual information from multiple data sources. Analyzing trajectory data through visualization improves the efficiency and accuracy of the analysis, yet it may induce exposure of the location privacy. To balance the location privacy and analysis effectiveness, this work focuses on the behaviors of different geo-based contexts in the process of trajectory interpretation. Three types of geo-based contexts are identified after surveying 94 related literatures. We further conduct experiments to investigate their capability by evaluating how they benefit the analysis, and whether they lead to location privacy exposure. Finally, we report and discuss interesting findings, and provide guidelines to the design of privacy-preserving analysis approaches for human periodic trajectories.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2018.2875021