Lclean: A Plausible Approach to Individual Trajectory Data Sanitization
Genre
Pre-printDate
2018-05-06Author
Han, QLu, D
Zhang, K
Du, X
Guizani, M
Permanent link to this record
http://hdl.handle.net/20.500.12613/4668
Metadata
Show full item recordDOI
10.1109/ACCESS.2018.2833163Abstract
© 2013 IEEE. In recent years, with the continuous development of significant data industrialization, trajectory data have more and more critical analytical value for urban construction and environmental monitoring. However, the trajectory contains a lot of personal privacy, and rashly publishing trajectory data set will cause serious privacy leakage risk. At present, the privacy protection of trajectory data mainly uses the methods of data anonymity and generalization, without considering the background knowledge of attackers and ignores the risk of adjacent location points may leak sensitive location points. In this paper, based on the above problems, combined with the location correlation of trajectory data, we proposed a plausible replacement method. First, the correlation of trajectory points is proposed to classify the individual trajectories containing sensitive points. Then, according to the relevance of location points and the randomized response mechanism, a reasonable candidate set is selected to replace the sensitive points in the trajectory to satisfy the locally differential privacy. Theoretical and experimental results show that the proposed method not only protects the sensitive information of individuals but also does not affect the overall data distribution.Citation to related work
Institute of Electrical and Electronics Engineers (IEEE)Has part
IEEE AccessADA compliance
For Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.eduae974a485f413a2113503eed53cd6c53
http://dx.doi.org/10.34944/dspace/4650