Research On Location Privacy Protection With Spatio-temporal Features In Social Networks

In a large number of social applications that have appeared in recent years,users can post current location information to social applications through location check-in services.Along with the large-scale use of the check-in services,social applications generate a lot of location check-in data and trajectory data.Aiming at the hidden location visit privacy leakage problem in the trajectory data,the location replacement technology can be used to reduce the confidence of leakage pattern,but the direct use of the location replacement technology will result in the anonymous data not meeting user behavior patterns and trajectory characteristic loss.This thesis defines the hidden location visit privacy protection problem for social networks with spatio-temporal features,and the Hidden Location Visit Privacy Protection algorithm is proposed.The basic idea is to anonymize certain trajectories that make a big contribution to privacy deduction,the hidden location visit privacy will be protected while ensuring that anonymous data can protect against more other forms of privacy attacks.Aiming at the problem that the anonymous trajectory does not match to user behavior patterns,the Location Categories Priority algorithm is proposed.By selecting the location candidate set belonging to the priority location category,the location transition of the new trajectory is more in line with user behavior patterns;aiming at the problem of trajectory characteristic loss,the Check Characteristic Preservation algorithm is proposed.The trajectory characteristic sequence is found by applying the principle of minimum description length,so that it can check whether the trajectory characteristic is lost before and after location replacement;a location selection strategy is designed to enable the algorithm to protect the location privacy while taking into account user behavior patterns and trajectory characteristic.Based on the real social network sign-in data set,the experiment is carried out and compared with the current related work.The experimental results show that the hidden location visit privacy protection algorithm proposed in this paper can effectively protect the hidden location visit privacy while ensuring that the anonymous trajectory is in line with the user behavior patterns and maintains the original trajectory characteristic.