Open AccessGraph Node Strength Histogram Publication Method with Node Differential Privacy
Author(s) -
Wenfen Liu,
Bixia Liu,
Qiang Xu,
Hui Lei
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1757/1/012186
Subject(s) - histogram , computer science , differential privacy , data publishing , node (physics) , merge (version control) , graph , algorithm , theoretical computer science , data mining , artificial intelligence , publishing , image (mathematics) , information retrieval , engineering , structural engineering , political science , law
The node differential privacy (node-DP) can be used to protect the private information of nodes and edges in the graph. In this paper, we propose an algorithm of publishing node strength histogram under node-DP, which could improve the accuracy of publishing the node strength histogram. In this algorithm, we use the Sequence Edge removal to reduce the sensitivity of query function and restrict the weight of edges to make the distribution of node strength denser. Furthermore, we use the histogram grouping algorithm Hierarchical Cluster Grouping to group the buckets to merge buckets with close values into one group. The experiments show that our algorithm maintains higher data utility than those traditional histogram publishing algorithms under the same privacy budget.