恶意软件传播的SEIRS流行病模型的全局动态

Soodeh Hosseini, M. A. Azgomi, A. Rahmani
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引用次数: 3

摘要

本文试图建立一个易感-暴露-感染-恢复-易感(SEIRS)流行病模型,以研究无标度网络(SFNs)中恶意软件传播的动态行为。在提出的离散时间流行病模型中,我们考虑了软件多样性的防御机制来限制流行病在SFNs中的传播。SEIRS流行病模型的动力学行为由基本繁殖比决定,基本繁殖比常被用作阈值参数。此外,还研究了不同软件包的分配对传播过程的影响。理论结果表明,基本繁殖比对不同的软件包和网络拓扑结构有显著的依赖性。在节点上安装不同的软件包会降低繁殖率和恶意软件的传播。数值模拟结果验证了理论分析的正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the global dynamics of an SEIRS epidemic model of malware propagation
In this paper, we attempt to mathematically formulate a susceptible-exposed-infectious-recovered-susceptible (SEIRS) epidemic model to study dynamical behaviors of malware propagation in scale-free networks (SFNs). In the proposed discrete-time epidemic model, we consider defense mechanism of software diversity to limit epidemic spreading in SFNs. Dynamical behaviors of the SEIRS epidemic model is determined by basic reproductive ratio, which is often used as a threshold parameter. Also, the impact of the assignment of diverse software packages on the propagation process is examined. Theoretical results show that basic reproductive ratio is significantly dependent on diverse software packages and the network topology. The installation of diverse software packages on nodes leads to decrease reproductive ratio and malware spreading. The results of numerical simulations are given to validate the theoretical analysis.
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