PDGM: Percolation-based directed graph matching in social networks

Author(s):  
Lijing Wang ◽  
Jin-Hee Cho ◽  
Ing-Ray Chen ◽  
Jiangzhuo Chen
2021 ◽  
pp. 110-118
Author(s):  
Hongyan Zhang ◽  
Xiaolin Li ◽  
Jiayu Xu ◽  
Li Xu

It is interesting to look at the types of social networks that are directed or weighted, or social networks with the combination of both. In many cases, the relationship between vertices may be quantifiable (weighted) or asymmetrical (directed). In this chapter, the authors first introduce the concept of weighted social networks and present an anonymization algorithm for these networks called the anonymity generalization algorithm. After that, they discuss k-anonymous path privacy and introduce the MSP algorithm. Next, the authors introduce the (k1, k2)-shortest path privacy and a (k1, k2)-shortest path privacy algorithm. Then they introduce directed weighted social networks and present the k-multiple paths anonymization on PV+NV (KMPPN). Also, the authors present a technique to convert directed networks into undirected networks. Finally, the authors present the linear property preserving anonymization approach for social networks.


Author(s):  
Kirk Ogaard ◽  
Heather Roy ◽  
Sue Kase ◽  
Rakesh Nagi ◽  
Kedar Sambhoos ◽  
...  

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Tieying Zhu ◽  
Shanshan Wang ◽  
Xiangtao Li ◽  
Zhiguo Zhou ◽  
Riming Zhang

With the rapid development of social networks and its applications, the demand of publishing and sharing social network data for the purpose of commercial or research is increasing. However, the disclosure risks of sensitive information of social network users are also arising. The paper proposes an effective structural attack to deanonymize social graph data. The attack uses the cumulative degree ofn-hop neighbors of a node as the regional feature and combines it with the simulated annealing-based graph matching method to explore the nodes reidentification in anonymous social graphs. The simulation results on two social network datasets show that the attack is feasible in the nodes reidentification in anonymous graphs including the simply anonymous graph, randomized graph andk-isomorphism graph.


2018 ◽  
Vol 12 (2) ◽  
pp. 1-39 ◽  
Author(s):  
Carla-Fabiana Chiasserini ◽  
Michel Garetto ◽  
Emili Leonardi

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