Personalized Privacy Protection Mechanism Integrating Spatiotemporal Correlation

Abstract

In view of the insufficient data availability in traditional trajectory privacy protection schemes, in order to achieve a balance between privacy security and data usage efficiency. This paper achieves personalization of privacy protection and optimization of data availability by comprehensively considering sensitive locations and their correlations in user trajectories. It can realize personalized protection of sensitive locations with different privacy levels based on the user’s preset privacy needs and sensitivity assessment. At the same time, by introducing trajectory candidate sets and cross-correlation functions, a new trajectory publishing mechanism is constructed, which can maintain the spatiotemporal characteristics of trajectory data while ensuring privacy. Through simulation experiments, the effectiveness of the proposed scheme was verified on real data sets. Experimental results show that the method proposed in this article has good results in terms of privacy protection strength and data availability.