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- Title
Efficient Location Privacy-Preserving k-Anonymity Method Based on the Credible Chain.
- Authors
Hui Wang; Haiping Huang; Yuxiang Qin; Yunqi Wang; Min Wu
- Abstract
Currently, although prevalent location privacy methods based on k-anonymizing spatial regions (K-ASRs) can achieve privacy protection by sacrificing the quality of service (QoS), users cannot obtain accurate query results. To address this problem, it proposes a new location privacy-preserving k-anonymity method based on the credible chain with two major features. First, the optimal k value for the current user is determined according to the user's environment and social attributes. Second, rather than forming an anonymizing spatial region (ASR), the trusted third party (TTP) generates a fake trajectory that contains k location nodes based on properties of the credible chain. In addition, location-based services (LBS) queries are conducted based on the trajectory, and privacy level is evaluated by instancing θ privacy. Simulation results and experimental analysis demonstrate the effectiveness and availability of the proposed method. Compared with methods based on ASR, the proposed method guarantees 100% QoS.
- Subjects
LOCATION-based services; QUALITY of service; SOCIAL attitudes
- Publication
ISPRS International Journal of Geo-Information, 2017, Vol 6, Issue 6, p163
- ISSN
2220-9964
- Publication type
Article
- DOI
10.3390/ijgi6060163