考虑良性蠕虫和链路预测方法的复杂网络中蠕虫传播模型动力学

IF 2 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Engineering reports : open access Pub Date : 2025-02-20 DOI:10.1002/eng2.13110
Elham Asadi, Soodeh Hosseini
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引用次数: 0

摘要

本文采用流行模型对蠕虫作为一种恶意软件的传播进行建模。在提出的模型中,我们考虑了良性蠕虫的防御机制,链路预测和感染节点的隔离作为减少蠕虫在复杂网络中的传播的方法。对于良性蠕虫,我们考虑了检测脆弱节点的能力和免疫节点的能力参数,并研究了它们在减少蠕虫在网络中的传播中的作用。将良性蠕虫的漏洞列表作为良性蠕虫的另一个特征,分析其在蠕虫传播中的作用。在对模型进行动态分析的基础上,得到了模型的初始平衡点和基本再生比。最后,在Barabasi Albert人工网络和标准数据集上对该模型进行了评估,并与SIR和SIRV模型进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Dynamics of Worm Propagation Model in Complex Networks Considering Benign Worm and Link Prediction Approach

In this paper, the spread of worms as a type of malware is modeled with epidemic models. In the proposed model, we have considered the defense mechanism of the benign worm, link prediction, and quarantine of the infected nodes as methods to reduce the spread of the worm in complex networks. For the benign worm, the parameters of the ability to detect vulnerable nodes and the ability to immunization nodes have been considered, and we have investigated their role in reducing the spread of the worm in the network. The vulnerability list of the benign worm is considered as another characteristic of the benign worm and its role in the spread of the worm is analyzed. In the context of dynamic analysis of the model, we have obtained the initial equilibrium point and the basic reproduction ratio. Finally, the proposed model is evaluated on the Barabasi Albert artificial network and the standard data sets and compared with the SIR and SIRV models.

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5.10
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审稿时长
19 weeks
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