2019 Scientific Conference on Network, Power Systems and Computing
A Privacy Protection Method for Social Networks Based on Node Importance
CUI Haitao, LI Lingjuan
The social networks record a large amount of social activities information, which contain sensitive data and private information. It makes social networks more vulnerable to be attacked. In order to resist the attacks based on structural knowledge and better protect the privacy information, this paper designs a privacy protection method for social networks based on node importance (NI-PP). This method introduces the node importance calculated by K-shell into K-symmetric anonymity to realize the purpose of protecting important nodes and provides a new restoration algorithm that can completely restore the structures of the original networks. This restoration algorithm uses labels added on the original networks to recover those nodes that are deleted mistakenly during the restoration process, so as to improve the availability of the anonymous networks and reduce the loss of information in the restoration process. Analysis and experiments results show that NI-PP can protect the privacy information of social networks very well.
Social network, privacy protection, K-shell, K-symmetric anonymity
Cite this paper:
CUI Haitao, LI Lingjuan, A Privacy Protection Method for Social Networks Based on Node Importance. 2019 Scientific Conference on Network, Power Systems and Computing (NPSC 2019), 2019: 152-155. DOI: https://doi.org/10.33969/EECS.V3.035.