LBS user location privacy protection scheme based on trajectory similarity

Abstract

Abstract During the data set input or output, or the data set itself adds noise to enable data distortion to effectively reduce the risk of user privacy leakage. However, in the conventional method, the added noise may cause data distortion, thereby appealed against it. However, the amount of noise is too small and cannot meet the effect of privacy protection. Therefore, we propose a LBS user location privacy protection scheme based on trajectory similarity (DPTS). With double privacy protection without reducing the efficiency of algorithms, it does not cause data distortion to provide more reliable privacy protection. The main contributions of this article include: (1) In the process of collecting and publishing the location data, introduce into the privacy protection method, (2) The differential privacy algorithm based on the trajectory prefix tree is superimposed on the basis of the false position replacement algorithm based on the trajectory similarity, (3) Propose LBS-based Difference Privacy Protection Algorithm. In the algorithm, We reach the purpose of protecting user personal privacy by replace the original trajectory into a fake track trace that is the lowest degree of similarity in the interval. Then establish a prefix tree and add noise to the positional frequency. It is in order to further protect the sensitive location information, double protection in the trajectory data set, and the degree of privacy protection is improved. Simulation experiment results show that the proposed algorithm is effective. The algorithm can suppress the distortion rate of data while improving the amount of noise, and in improving the algorithm operation efficiency, it reduces the risk of leakage of sensitive position information.