Estimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks

Sensors

Tai-Hoon Kim¹  Ana Lucila Sandoval Orozco²  Luis Javier García Villalba²  Javier Portela²  Alejandra Guadalupe Silva Trujillo² 

[1] Department of Convergence Security, Sungshin Women’s University, 249-1 Dongseon-dong 3-ga, Seoul 136-742, Korea;Group of Analysis, Security and Systems (GASS), Department of Software Engineering and Artificial Intelligence (DISIA), Faculty of Information Technology and Computer Science, Office 431, Universidad Complutense de Madrid (UCM), Calle Profesor José García Santesmases, 9, Ciudad Universitaria, Madrid 28040, Spain;

关键词: anonymity;    email network;    graph theory;    privacy;    social network analysis;    small-world-ness;    statistical disclosure attack;   

DOI  :  10.3390/s16111832

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown