Modeling Social Engineering Botnet Dynamics across Multiple Social Networks

Abstract : In recent years, widely spreading botnets in social networks are becoming a major security threat to both social networking services and the privacy of their users. In order to have a better understanding of the dynamics of these botnets, defenders should model the process of their propagation. However, previous studies on botnet propagation model have tended to focus solely on characterizing the vulnerability propagation on one infection domain, and left two key properties (cross-domain mobility and user dynamics) untouched. In this paper, we formalize a new propagation model to reveal the general infection process of social engineering botnets in multiple social networks. This proposed model is based on stochastic process, and investigates two important factors involved in botnet propagation: (i)bot spreading across multiple domains, and (ii)user behaviors in social networks. Furthermore, with statistical data obtained from four real-world social networks, a botnet simulation platform is built based on OMNeT++ to test the validity of our model. The experimental results indicate that our model can accurately predict the infection process of these new advanced botnets with less than 5% deviation.
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Conference papers
Dimitris Gritzalis; Steven Furnell; Marianthi Theoharidou. 27th Information Security and Privacy Conference (SEC), Jun 2012, Heraklion, Crete, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-376, pp.261-272, 2012, Information Security and Privacy Research. 〈10.1007/978-3-642-30436-1_22〉
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Shuhao Li, Xiaochun Yun, Zhiyu Hao, Yongzheng Zhang, Xiang Cui, et al.. Modeling Social Engineering Botnet Dynamics across Multiple Social Networks. Dimitris Gritzalis; Steven Furnell; Marianthi Theoharidou. 27th Information Security and Privacy Conference (SEC), Jun 2012, Heraklion, Crete, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-376, pp.261-272, 2012, Information Security and Privacy Research. 〈10.1007/978-3-642-30436-1_22〉. 〈hal-01518260〉

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