The Interactive Query Method with Clustering and Differential Privacy Protection Model Under Big Data Environment

To enhance the privacy protection as well as to improve data availability, a differential privacy data protection approach is proposed. Through big data cross-platform query, differential privacy method is performed on the results of ICMD (insensitive clustering method for mixed data) based on the insensitive clustering algorithm. The combination of clustering and differential privacy achieves the distinction of query sensitivity from a single record to a group of records. In addition, to meet the requirements of maintaining differential privacy for mixed data, this paper uses different methods to calculate the distance and centroid of classification and numerical attributes. Finally, the experiment shows the validity of the method, which reduces the risk of information loss and leakage.