Research Article
Differential Private Trajectory Obfuscation
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@INPROCEEDINGS{10.1007/978-3-642-40238-8_12, author={Roland Assam and Marwan Hassani and Thomas Seidl}, title={Differential Private Trajectory Obfuscation}, proceedings={Mobile and Ubiquitous Systems: Computing, Networking, and Services. 9th International Conference, MobiQuitous 2012, Beijing, China, December 12-14, 2012. Revised Selected Papers}, proceedings_a={MOBIQUITOUS}, year={2013}, month={9}, keywords={Spatial Database LBS Differential Privacy}, doi={10.1007/978-3-642-40238-8_12} }- Roland Assam
Marwan Hassani
Thomas Seidl
Year: 2013
Differential Private Trajectory Obfuscation
MOBIQUITOUS
Springer
DOI: 10.1007/978-3-642-40238-8_12
Abstract
We propose a novel technique to ensure location privacy for mobility data using differential privacy. Privacy is guaranteed through path perturbation by injecting noise to both the space and time domain of a spatio-temporal data. In addition, we present to the best of our knowledge, the first context aware differential private algorithm. We conducted numerous experiments on real and synthetic datasets, and show that our approach produces superior privacy results when compared to state-of-the-art techniques.
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