Efficient publication of distributed and overlapping graph data under differential privacy

Graph data publication has been considered as an important step for data analysis and mining. Graph data, which provide knowledge on interactions among entities, can be locally generated and held by distributed data owners. These data are usually sensitive and private, because they may be related to owners' personal activities and can be hijacked by adversaries to conduct inference attacks. Curren...