Abstract
Now many applications of location data have facilitated people’s daily life. However, publishing location data may divulge individual sensitive information so as to influence people’s normal life. On the other hand, if we cannot mine and share location data information, location data will lose its value to serve our society. Currently, as the records about trajectory data may be discrete in database, some existing privacy protection schemes are difficult to protect trajectory data. In this paper, we propose a trajectory data privacy protection scheme based on differential privacy mechanism. In the proposed scheme, the algorithm first selects the protected points from the user’s trajectory data; secondly, the algorithm forms the polygon according to the protected points and the adjacent and high frequent accessed points that are selected from the accessing point database, then the algorithm calculates the polygon centroids; finally, the noises are added to the polygon centroids by the differential privacy method, and the polygon centroids replace the protected points, and then the algorithm constructs and issues the new trajectory data. The experiments show that the running time of the proposed algorithms is fast, the privacy protection of the scheme is effective and the data usability of the scheme is higher.
Highlights
1.1 BackgroundWith the rapid development of computer and network, data mining and analysis plays an increasingly important role in our social life
We propose a trajectory data privacy protection scheme based on Laplace’s differential privacy mechanism
The algorithm first selects the protected points from the user’s trajectory data; secondly, the algorithm builds the polygons according to the protected points and the adjacent and high frequent accessed points selected from the accessed point database, the algorithm calculates the polygon centroids; the noises are added to the polygon centroids by the Laplace’ differential privacy method, and the new polygon centroids are used to replace the protected points, and the algorithm constructs and issues the new trajectory data
Summary
With the rapid development of computer and network, data mining and analysis plays an increasingly important role in our social life. Trajectory data is mainly collected and disseminated by mobile equipments, but many mobile devices and mobile communication technologies must integrate geographical data and individual information into trajectory data, such as individual information may contain individual privacy data, personal health status, social status and behavior habits, etc, mining and publishing trajectory data may divulge individual sensitive information so as to influence people’s normal life [2,3,4] It is the key of trajectory data privacy protection that how to protect sensitive trajectory data while providing trajectory information service on data mining. We focus on finding an efficient privacy protection scheme for trajectory data in this paper
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