Research On Privacy Protection Method Based On Trace K-anonymity

With the continuous innovation of wireless location technology and the large-scale popularization of mobile intelligent terminal equipment,a large number of track data related to mobile objects are saved in different forms by LBSP(Location Based Services Provider).When the service provider provides services for mobile objects,it is inevitable that some malicious attackers will steal these trace data by improper means.By analyzing,filtering and predicting the trajectory data,the personal privacy information or trajectory privacy information of mobile objects can be inferred.At present,the leakage of trajectory information of mobile objects leads to more and more events that threaten their own security,and the privacy information and trajectory data of mobile objects are paid more and more attention.The purpose of this paper is to further research and explore the defects in the existing track privacy protection technology.The main process is as follows:First,based on the analysis of the existing track privacy protection technology,a track anonymity algorithm for location region division is proposed.According to the starting and ending time,the algorithm searches for the sensitive area of the current time through the k-anonymity set of synchronization track,and merges the area if the distance between the divided sub area and the adjacent anonymity area is not greater than the threshold d.Otherwise,we use the location mapping strategy to add false location in the sub region according to the original location to meet the k-anonymity principle.The false position keeps the relative position relationship of each point in the sensitive area,which makes the sub area and the original area anonymous.Experimental results show that compared with the existing track anonymity algorithm,the algorithm further reduces the risk of track privacy disclosure,and effectively improves the availability of track anonymity data set.Second,most of the existing trajectory privacy protection technologies protect the static trajectory data of mobile objects,but ignore the risk of privacy disclosure of the dynamic trajectory of mobile objects.In order to solve this problem,the research of dynamic trajectory anonymity based on genetic algorithm is proposed.The algorithm uses the characteristics of genetic algorithm to search the global optimal solution,establishes the track behavior mode in the current historical track of the moving object,forecasts the track of the moving object through the track behavior mode,and constantly updates the track behavior mode according to the new predicted track of the moving object,so that the accuracy of track prediction is higher.In order to protect the privacy information of the mobile object,we use k-anonymity technology to generate the false trajectory for the new prediction trajectory.Experiments show that compared with the existing track anonymity algorithm,the algorithm in this paper can protect the privacy of the track and further improve the quality of the track data.The main purpose of this paper is to reduce the risk of privacy disclosure of track anonymous data set,further protect the track privacy of mobile objects,and improve the availability of track anonymous data set after release.According to the needs of moving objects in different scenes,different privacy protection strategies are adopted for static and dynamic track data of moving objects.The experimental results show that the algorithm proposed in this paper has a further improvement in track privacy protection and track data availability.