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2018-06-20
Jiao, L., Yin, H., Guo, D., Lyu, Y..  2017.  Heterogeneous Malware Spread Process in Star Network. 2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW). :265–269.

The heterogeneous SIS model for virus spread in any finite size graph characterizes the influence of factors of SIS model and could be analyzed by the extended N-Intertwined model introduced in [1]. We specifically focus on the heterogeneous virus spread in the star network in this paper. The epidemic threshold and the average meta-stable state fraction of infected nodes are derived for virus spread in the star network. Our results illustrate the effect of the factors of SIS model on the steady state infection.

2014-09-17
Han, Yujuan, Lu, Wenlian, Xu, Shouhuai.  2014.  Characterizing the Power of Moving Target Defense via Cyber Epidemic Dynamics. Proceedings of the 2014 Symposium and Bootcamp on the Science of Security. :10:1–10:12.

Moving Target Defense (MTD) can enhance the resilience of cyber systems against attacks. Although there have been many MTD techniques, there is no systematic understanding and quantitative characterization of the power of MTD. In this paper, we propose to use a cyber epidemic dynamics approach to characterize the power of MTD. We define and investigate two complementary measures that are applicable when the defender aims to deploy MTD to achieve a certain security goal. One measure emphasizes the maximum portion of time during which the system can afford to stay in an undesired configuration (or posture), without considering the cost of deploying MTD. The other measure emphasizes the minimum cost of deploying MTD, while accommodating that the system has to stay in an undesired configuration (or posture) for a given portion of time. Our analytic studies lead to algorithms for optimally deploying MTD.