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A novel dynamic model for web malware spreading over scale-free networks

机译:无规模网络传播的Web恶意软件的新动态模型

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摘要

The complex properties of real-world systems have been found in a wide range of physical and social networks. In this paper, a novel network-based model is developed to theoretically address the structure impact of scale-free networks on epidemic web malware spreading. We further split the compartments of the SDIRS model in terms of node degree, and apply the degree-based mean-field approach to formulate the model. The spreading threshold of the new model is explicitly calculated, and the global stability of the malware-free equilibrium is theoretically addressed provided the threshold below unity. Numerical simulations are given to illustrate the theoretical results. Moreover, the dynamics around the malware equilibrium and parameter analysis are also discussed by designing some numerical examples. The predictions are generally in agreement with numerical simulation results. Consequently, we suggest that web malware can be availably contained by properly adjusting the network structure so that the propagation threshold is less than unity. (C) 2018 Elsevier B.V. All rights reserved.
机译:在广泛的物理和社交网络中发现了现实系统的复杂性质。在本文中,开发了一种基于新的基于网络的模型,从理论上解决了无规模网络对流行性网络恶意软件传播的结构影响。我们在节点度方面进一步分离了SDIRS模型的隔间,并应用了基于程度的平均场方法来制定模型。明确计算新模型的扩展阈值,从理论上解决了恶意软件平衡的全局稳定性提供了低于统一的阈值。给出了数值模拟来说明理论结果。此外,还通过设计一些数值示例来讨论恶意软件平衡和参数分析周围的动态。预测通常与数值模拟结果一致。因此,我们建议通过正确调整网络结构,以便妥善调整网络恶意软件,使得传播阈值小于Unity。 (c)2018年elestvier b.v.保留所有权利。

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