Degree Histogram Publishing Method of Dynamic Graph Data Based on Node Differential Privacy

Dynamic graph data can not only reveal the rules of network evolution, but also contain a large amount of personal privacy information. The degree of nodes is an important indicator to analyze the relationship between nodes in the network and to quantify the status of nodes. From the node degree histogram of the dynamic network, we can obtain information such as key nodes and network structure, but there is also the risk of leaking user privacy information. This paper studies the degree histogram publishing method of dynamic graph data based on node differential privacy. And abstracts dynamic graph data into incremental graph data. Aiming at the problem of high sensitivity of query functions, a pretreatment method based on graph projection technology is proposed.On this basis, we use a hierarchical clustering algorithm to group the difference sequences of the histogram sequence. Finally, combining the above two methods, we give a method for publishing the degree histogram of dynamic graph data based on node difference privacy. Simulation experiments show that the algorithm proposed in this paper not only guarantees the privacy of the data, but also improves the utility of the released data.