Privacy-Preserving Method for Trajectory Data Publication Based on Local Preferential Anonymity
With the rapid development of mobile positioning technologies, location-based services (LBSs) have become more widely used. The amount of user location information collected and applied has increased, and if these datasets are directly released, attackers may infer other unknown locations through pa...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2078-2489/14/3/157 |
| _version_ | 1827749431266508800 |
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| author | Xiao Zhang Yonglong Luo Qingying Yu Lina Xu Zhonghao Lu |
| author_facet | Xiao Zhang Yonglong Luo Qingying Yu Lina Xu Zhonghao Lu |
| author_sort | Xiao Zhang |
| collection | DOAJ |
| description | With the rapid development of mobile positioning technologies, location-based services (LBSs) have become more widely used. The amount of user location information collected and applied has increased, and if these datasets are directly released, attackers may infer other unknown locations through partial background knowledge in their possession. To solve this problem, a privacy-preserving method for trajectory data publication based on local preferential anonymity (LPA) is proposed. First, the method considers suppression, splitting, and dummy trajectory adding as candidate techniques. Second, a local preferential (LP) function based on the analysis of location loss and anonymity gain is designed to effectively select an anonymity technique for each anonymous operation. Theoretical analysis and experimental results show that the proposed method can effectively protect the privacy of trajectory data and improve the utility of anonymous datasets. |
| first_indexed | 2024-03-11T06:24:00Z |
| format | Article |
| id | doaj.art-687cc371fbd142169ecd6ea18c04674e |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-11T06:24:00Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-687cc371fbd142169ecd6ea18c04674e2023-11-17T11:43:53ZengMDPI AGInformation2078-24892023-03-0114315710.3390/info14030157Privacy-Preserving Method for Trajectory Data Publication Based on Local Preferential AnonymityXiao Zhang0Yonglong Luo1Qingying Yu2Lina Xu3Zhonghao Lu4School of Computer and Information, Anhui Normal University, Wuhu 241003, ChinaSchool of Computer and Information, Anhui Normal University, Wuhu 241003, ChinaSchool of Computer and Information, Anhui Normal University, Wuhu 241003, ChinaSchool of Computer and Information, Anhui Normal University, Wuhu 241003, ChinaSchool of Computer and Information, Anhui Normal University, Wuhu 241003, ChinaWith the rapid development of mobile positioning technologies, location-based services (LBSs) have become more widely used. The amount of user location information collected and applied has increased, and if these datasets are directly released, attackers may infer other unknown locations through partial background knowledge in their possession. To solve this problem, a privacy-preserving method for trajectory data publication based on local preferential anonymity (LPA) is proposed. First, the method considers suppression, splitting, and dummy trajectory adding as candidate techniques. Second, a local preferential (LP) function based on the analysis of location loss and anonymity gain is designed to effectively select an anonymity technique for each anonymous operation. Theoretical analysis and experimental results show that the proposed method can effectively protect the privacy of trajectory data and improve the utility of anonymous datasets.https://www.mdpi.com/2078-2489/14/3/157data processingtrajectory anonymityprivacy preservationsplittingsuppressiondummy trajectory |
| spellingShingle | Xiao Zhang Yonglong Luo Qingying Yu Lina Xu Zhonghao Lu Privacy-Preserving Method for Trajectory Data Publication Based on Local Preferential Anonymity Information data processing trajectory anonymity privacy preservation splitting suppression dummy trajectory |
| title | Privacy-Preserving Method for Trajectory Data Publication Based on Local Preferential Anonymity |
| title_full | Privacy-Preserving Method for Trajectory Data Publication Based on Local Preferential Anonymity |
| title_fullStr | Privacy-Preserving Method for Trajectory Data Publication Based on Local Preferential Anonymity |
| title_full_unstemmed | Privacy-Preserving Method for Trajectory Data Publication Based on Local Preferential Anonymity |
| title_short | Privacy-Preserving Method for Trajectory Data Publication Based on Local Preferential Anonymity |
| title_sort | privacy preserving method for trajectory data publication based on local preferential anonymity |
| topic | data processing trajectory anonymity privacy preservation splitting suppression dummy trajectory |
| url | https://www.mdpi.com/2078-2489/14/3/157 |
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