Privacy Preserving in Online Social Networks Using Fuzzy Rewiring

被引:11
作者
Kumar, Saurabh [1 ]
Kumar, Pradeep [2 ]
机构
[1] Indian Inst Management Indore, Indore 453556, India
[2] Indian Inst Management Lucknow, Lucknow 226013, Uttar Pradesh, India
关键词
Social networking (online); Privacy; Fuzzy sets; Data privacy; Clustering algorithms; Task analysis; Perturbation methods; Fuzzy set; graph publishing; online social network (OSN); privacy-preserving; rewiring; ANONYMITY; REIDENTIFICATION; ANONYMIZATION; GRAPHS; TIME;
D O I
10.1109/TEM.2021.3072812
中图分类号
F [经济];
学科分类号
02 ;
摘要
Privacy concerns of users threaten the usage of online social networks (OSN). In this regard, privacy preserving of OSN emerged as a convincing solution for preserving the privacy of users and uncovering useful insights from the social network data. In this article, we propose a novel algorithm based on the fuzzy sets and rewiring algorithm for preserving the privacy of users. This article presents the algorithm called privacy-preserving rewiring algorithm (PPRA), which can be used for anonymizing the social network data. The algorithm is validated by showing its effectiveness on four real-world datasets across three major graph mining tasks. The proposed PPRA algorithm will help in preserving the privacy of users in the OSN graph while simultaneously maintaining the utility that can be generated from the OSN graph structure.
引用
收藏
页码:2071 / 2079
页数:9
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