Macroscopic Malware Propagation Dynamics for Complex Networks With Churn

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Abstract
In this letter, a queueing-based approach for modeling malware propagation in complex networks with churn (dynamic node variation) is introduced. The proposed methodology captures the dynamics of SIS-type malware, especially in time-varying networks, where nodes enter and leave due to their limited energy reserves, or as the outcome of malware attacks. We demonstrate the developed model in various complex networks, showing how it can be exploited for analytically quantifying network reliability and further used for increasing the robustness of the network against generic malware attacks.

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