Privacy Protection Method for Cellular Signaling Data Based on Genetic Algorithm
Cellular signaling data (CSD) is a new data source of intelligent transportation and has great potential in the study of human mobility. However, research recently has shown that the privacy of individual trajectories of travelers can be easily leaked due to their unique travel patterns, which will lead to the disclosure of a traveler’s trajectory privacy. To address this issue, the risk of privacy leakage in a CSD data set was quantitatively measured due to reidentification attacks. To reduce the risk of trajectory privacy leakage, a spatial generalization method based on an improved genetic algorithm (IGA) was proposed. The authors transformed the base station aggregation problem that meets the k-anonymity requirement into a shortest path problem. The data utility loss after privacy preservation was evaluated based on origin–destination (OD) flow analysis of traffic analysis zones (TAZs). Finally, the relationships between privacy preservation and data utility were revealed. In all of the cases, more privacy protection corresponded to less data utility. The discovered relationships provide useful guidance for data publishers on how to choose the right tradeoff between privacy protection and data utility when publishing or sharing such sensitive data.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/24732907
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Supplemental Notes:
- © 2023 American Society of Civil Engineers.
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Authors:
- Chen, Hua
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0000-0003-1397-2637
- Cai, Ming
- Chen, Xiong
- Publication Date: 2023-4
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: 04023016
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Serial:
- Journal of Transportation Engineering, Part A: Systems
- Volume: 149
- Issue Number: 4
- Publisher: American Society of Civil Engineers
- ISSN: 2473-2907
- EISSN: 2473-2893
- Serial URL: http://ascelibrary.org/journal/jtepbs
Subject/Index Terms
- TRT Terms: Cellular telephones; Data mining; Data privacy; Genetic algorithms; Origin and destination; Travel patterns
- Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; Society;
Filing Info
- Accession Number: 01876766
- Record Type: Publication
- Files: TRIS, ASCE
- Created Date: Mar 23 2023 10:20AM