Upper approximation based privacy preserving in online social networks

作者：

Highlights：

• A rough set based privacy preserving graph publishing algorithm has been proposed.

• The algorithm is effective for clustering, classification, and PageRank computation.

• Experiments were done on four real-world standard datasets.

• The algorithm maintains both privacy of individuals and accuracy of graph mining tasks.

摘要

•A rough set based privacy preserving graph publishing algorithm has been proposed.•The algorithm is effective for clustering, classification, and PageRank computation.•Experiments were done on four real-world standard datasets.•The algorithm maintains both privacy of individuals and accuracy of graph mining tasks.

论文关键词：Rough-sets,Privacy preserving,Graph publishing,Online social network

论文评审过程：Received 11 April 2017, Revised 18 June 2017, Accepted 10 July 2017, Available online 11 July 2017, Version of Record 17 July 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.07.010