Estimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks



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Portela García-Miguel, Javier and García Villalba, Luis Javier and Silva Trujillo, Alejandra Guadalupe and Sandoval Orozco, Ana Lucila and Kim, Tai-Hoon (2016) Estimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks. Sensors, 16 (11). p. 1832. ISSN 1424-8220

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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.

Item Type:Article
Uncontrolled Keywords:anonymity; email network; graph theory; privacy; social network analysis; small-world-ness; statistical disclosure attack
Subjects:Sciences > Computer science > Networks
Sciences > Statistics
ID Code:67732
Deposited On:09 Sep 2021 11:56
Last Modified:09 Sep 2021 11:59

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