Optimal anonymous location privacy protection algorithm based on grid user density

ABSTRACT

The existing location anonymity algorithms do not consider the distribution of user density in the region. The area of anonymous domain is not the most appropriate and the query workload is redundant. To solve this problem, this paper proposes optimal anonymous location privacy protection algorithm based on grid user density. Taking the user density of the regional grid as the core and using reasonable dynamic shrinkage and expansion rules to find the most suitable anonymous domain, and reduces the anonymous domain as much as possible to meet the user privacy parameter configuration, thereby improving LBS service quality. This paper builds simulation dataset based on road network moving objects, and simulation experiments are performed on location privacy protection method, which proves the effectiveness of this method. At the same time, the real road network floating vehicle data is selected for the application of algorithm, which proves the feasibility of this method.

KEYWORDS:

• Privacy protection
• anonymous location
• grid user density
• LBS service
• privacy level‌
• service quality‌
• Q-Tree spatial index
• central anonymizer‌

Acknowledgements

We thank Senior Eng. Yilong Xiao for excellent technical support and valuable discussion.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes on contributors

Yalin Miao is an Associate professor of signal and information processing in Xi'an University of Technology. The main research interest covers image processing, computer vision, computer language and deep learning.

Huanhuan Jia is a Master student at Xi'an University of Technology. The main research interest covers computer vision, pattern recognition and network security.

Yang Zhang is a Master student at Xi'an University of Technology. The main research interest covers computer language, pattern recognition and network security.

Xuemin Liu is a Master student at Xi'an University of Technology. The main research interest covers computer language, pattern recognition and network security.

Tiantian Ji is a Master student at Xi'an University of Technology. The main research interest covers pattern recognition and network security.

Additional information

Funding

This work was supported by the Application Research of Font Generation Technology Based on Artificial Intelligence [grant number 2020JM-468], Shaanxi Natural Science Foundation.