How to preserve users' privacy information and minimize the loss of information when publishing trajectory data has become an important topic in the research field of privacy preservation. In this paper

we propose a trajectory privacy-preserving method based on single point gain

which satisfies the privacy requirements of users. According to the single point gain values

we suppress location points or add dummy trajectories into the trajectory dataset to ensure that the maximum benefit can be achieved at each iteration

thus reducing the loss of information. Theoretical analysis and experimental results show that

in the case of high privacy tolerance or a large number of attackers

the proposed method effectively reduces the information loss rate while guaranteeing the intensity of privacy preserving.