Location Data Quadtree Partitioning Algorithm Based on Differential Privacy

Due to the increasing demand for publishing spatial location data and the need to reduce errors in querying 2D spatial location data under differential privacy, differential privacy based quadtree partition publishing algorithm has already proposed. Firstly, constructing a quadtree satisfying differential privacy by the nodes of a 2D spatial dataset, second add laplace noise to partitioned region to satisfy differential privacy. Then, by using a heuristic judgment strategy to adjust DPQT from leaf node to root node from bottom to top to achieve a balance between uniform assumption error and noise error; Afterwards, post processing was performed on the noisy quadtree nodes using query consistency to further improve query accuracy. The article performed well in balancing the two types of errors, and finally, the query accuracy was analyzed horizontally by comparing the results on the dataset with other algorithms to verify the result of the algorithm proposed in this article.