Geospatial data based user privacy protection method and system

The invention provides a geospatial data based user privacy protection method and system. The method comprises: partitioning data space; combining similar cells to the same partition based on a uniformity measurement parameter; adding random noise conforming to Laplace distribution into each partition to obtain a noise data set; and externally providing a data query result based on the noise data set. The invention, based on analysis of noise errors and uniform assumption errors, proposes a novel data field granularity partitioning model for balancing the noise errors and the uniform assumption errors to minimize total data query errors. A condition that query is rectangular query is considered when the model is created, so that an actual data query condition is better met. Furthermore, the similar cells in the data space are combined, so that the query error of the geospatial data is smaller, and the data availability is greatly enhanced while the record security of user privacy is protected.