A novel privacy protection method based on node segmentation for social networks. (6th May 2022)

• Record Type: Journal Article
• Authors: Wang, Zhongli; Ju, Aiyun
• Is Part Of: International journal of communication networks and distributed systems. Volume 28:Number 4(2022)
• Page Start: 459
• Page End: 475
• Publication Date: 2022-05-06
• Subjects: social networks -- privacy protection -- node segmentation -- diameter distance; Computer networks -- Periodicals; Telecommunication systems -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; 004.6
• Languages: English
• ISSNs: 1754-3916

Abstract

In order to solve the problem of privacy disclosure of weight sequence in weighted social networks privacy protection, this paper proposes an anonymous weighted sequence method based on node segmentation to realise privacy protection of network structure, edge weight and weight sequence. In this method, the anonymity of edge weight sequence is realised mainly through the diameter distance within the group and the relative distance between nodes, which makes up for the privacy disclosure of weight sequence and improves the privacy protection mechanism of weighted social network. Under the premise of privacy security, this method can guarantee the structural features needed for social network analysis, the validity of the published data and the effective resistance to the attack of weight sequence. We also make comparison with other methods in terms of execution time and recognition rate, the results show that the proposed method can obtain shorter time and high node recognition.