Abstract
The dissemination of countermeasures is widely recognized as one of the most effective strategies of inhibiting malware propagation, and the study of general countermeasure and infection has an important and practical significance. On this point, a dynamical model incorporating generic nonlinear countermeasure and infection probabilities is proposed. Theoretical analysis shows that the model has a unique equilibrium which is globally asymptotically stable. Accordingly, a real network based on the model assumptions is constructed, and some numerical simulations are conducted on it. Simulations not only illustrate theoretical results but also demonstrate the reasonability of general countermeasure and infection.
Highlights
Introduction and Model FormulationHuman society has been subjected to great financial losses since malware constantly emerged (e.g., [1, 2]). e study of modeling and understanding malware spreading has attracted a lot of attention in the past three decades or so, and a multitude of propagation models capturing the behaviors of malware have been proposed
Yang and Yang [10] extended this model by incorporating the impacts of infected removable storage media and external nodes. These two models both neglect two important facts. They ignore the fact that the linear infection probability is a well fit for the real-world situations only when the infected nodes are few
Us, the assumptions of linear infection and countermeasure probabilities are unreasonable. To remedy these flaws and considering the impacts of general countermeasure and infection on the spread of malware, this paper studies a new dynamical model, which incorporates generic countermeasure and infection probabilities
Summary
Human society has been subjected to great financial losses since malware constantly emerged (e.g., [1, 2]). e study of modeling and understanding malware spreading has attracted a lot of attention in the past three decades or so, and a multitude of propagation models capturing the behaviors of malware have been proposed. Yang and Yang [10] extended this model by incorporating the impacts of infected removable storage media and external nodes (e.g., computers). Us, the assumptions of linear infection and countermeasure probabilities are unreasonable To remedy these flaws and considering the impacts of general countermeasure and infection on the spread of malware, this paper studies a new dynamical model (see Figure 1), which incorporates generic countermeasure and infection probabilities. S(t), I(t), and C(t) (S, I, and C, for short) denote the average numbers of susceptible, infected, and countermeasured internal nodes (i.e., nodes on the network) at time t, respectively. (H3) At time t, each infected or susceptible internal node obtains the newest countermeasure with probability c1(C(t)), where c1 is twice continuously differentiable, c1′ > 0, c1′′ < 0, and c1(0) 0.
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