%0 Journal Article
%A Portela García-Miguel, Javier
%A García Villalba, Luis Javier
%A Silva Trujillo, Alejandra Guadalupe
%A Sandoval Orozco, Ana Lucila
%A Kim, Tai-Hoon
%T Estimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks
%D 2016
%@ 1424-8220
%U https://hdl.handle.net/20.500.14352/19229
%X Social network analysis aims to obtain relational data from social systems to identify leaders, roles, and communities in order to model profiles or predict a specific behavior in users’ network. Preserving anonymity in social networks is a subject of major concern. Anonymity can be compromised by disclosing senders’ or receivers’ identity, message content, or sender-receiver relationships. Under strongly incomplete information, a statistical disclosure attack is used to estimate the network and node characteristics such as centrality and clustering measures, degree distribution, and small-world-ness. A database of email networks in 29 university faculties is used to study the method. A research on the small-world-ness and Power law characteristics of these email networks is also developed, helping to understand the behavior of small email networks.
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