Research Article
An Enhanced Location-Data Differential Privacy Protection Method Based on Filter
@INPROCEEDINGS{10.1007/978-3-031-20398-5_10, author={Shasha Zhang and Haiyan Kang and Dong Yu}, title={An Enhanced Location-Data Differential Privacy Protection Method Based on Filter}, proceedings={Smart Grid and Internet of Things. 5th EAI International Conference, SGIoT 2021, Virtual Event, December 18-19, 2021, Proceedings}, proceedings_a={SGIOT}, year={2022}, month={11}, keywords={Privacy protection Kalman filter Location-data Location based service Differential privacy}, doi={10.1007/978-3-031-20398-5_10} }- Shasha Zhang
Haiyan Kang
Dong Yu
Year: 2022
An Enhanced Location-Data Differential Privacy Protection Method Based on Filter
SGIOT
Springer
DOI: 10.1007/978-3-031-20398-5_10
Abstract
Location based service (LBS) is the basic function and important application of Internet of things. The disclosure of location data which contains a lot of sensitive information will be a threat for individual. This paper proposed an enhanced location-data differential privacy protection method based on filter. Firstly, noise is added in location-data for differential privacy. Secondly, Kalman is used to predict, correct and optimize the Location-data after the addition of noise, which ensure the optimization to satisfy the differential privacy. Finally, released the processed data and carry out the location query service. Experimental results demonstrate that the proposed algorithm promotes Location-data utility and level of privacy protection.
