A New Location Privacy Protection Algorithm

The accuracy of user location information is inversely proportional to the user's privacy preserving degree k, and is proportional to quality of query service. In order to balance the conflict between privacy preserving security and query quality caused by the accuracy of location information, A clustering algorithm aiming at eliminating outliers based on k-anonymity location privacy preserving model is proposed, which is used to realize the establishment of anonymous group in the anonymous model. The distribution of user in anonymous group is optimized. The idea of replacing the user location query by the center of the anonymous group is proposed, through the experimental analysis and comparison with other schemes, the number of repeated queries is reduced, and the quality of service query is improved on the premise of ensuring security.