
FOLLOWUS
1.Network and Information Center, Lanzhou University of Technology, Lanzhou 730000, China
2.Gansu Provincial Key Laboratory of Wearable Computing, Lanzhou 730000, China
3.School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
4.School of Computer Science and Artificial Intelligence, Lanzhou University of Technology, Lanzhou 730000, China
‡ Corresponding author
收稿:2024-03-29,
修回:2024-09-18,
网络出版:2025-09-05,
纸质出版:2025-09
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高凯, 张丽欣, 姚亚兵, 等. 终端边界防护对计算机病毒传播的影响:建模与仿真[J]. 信息与电子工程前沿(英文), 2025,26(9):1637-1648.
Kai GAO, Lixin ZHANG, Yabing YAO, et al. Effect of terminal boundary protection on the spread of computer viruses: modeling and simulation[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(9): 1637-1648.
高凯, 张丽欣, 姚亚兵, 等. 终端边界防护对计算机病毒传播的影响:建模与仿真[J]. 信息与电子工程前沿(英文), 2025,26(9):1637-1648. DOI: 10.1631/FITEE.2400236.
Kai GAO, Lixin ZHANG, Yabing YAO, et al. Effect of terminal boundary protection on the spread of computer viruses: modeling and simulation[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(9): 1637-1648. DOI: 10.1631/FITEE.2400236.
校园网络用户群体的多样性和复杂性增加了终端信息交互中感染计算机病毒的风险。因此,探究计算机病毒在这种网络中如何在终端之间传播至关重要。本文基于基础网络结构特性和经典传染病传播动力学模型,构建了一种适用于现实世界大学场景的全新计算机病毒传播模型。该模型包含六大群体:易感群体、未隔离潜伏群体、已隔离潜伏群体、感染群体、恢复群体、宕机群体。分析了该模型的基本再生数和无病平衡点。利用真实的高校终端计算机病毒传播数据,提出基本病毒感染率、基本病毒查杀率和安全防护策略部署率,以定义各群体间的转换概率并感知各群体的变化趋势。此外,基于提出的计算机病毒传播模型,分析了计算机病毒在校园网络中的传播趋势。提出抑制计算机病毒在终端传播的具体措施,最大程度确保校园网络终端安全稳定运行。
The diversity and complexity of the user population on the campus network increase the risk of computer virus infection during terminal information interactions. Therefore
it is crucial to explore how computer viruses propagate between terminals in such a network. In this study
we establish a novel computer virus spreading model based on the characteristics of the basic network structure and a classical epidemic-spreading dynamics model
adapted to real-world university scenarios. The proposed model contains six groups: susceptible
unisolated latent
isolated latent
infection
recovery
and crash. We analyze the proposed model's basic reproduction number and disease-free equilibrium point. Using real-world university terminal computer virus propagation data
a basic computer virus infection rate
a basic computer virus removal rate
and a security protection strategy deployment rate are proposed to define the conversion probability of each group and perceive each group's variation tendency. Furthermore
we analyze the spreading trend of computer viruses in the campus network in terms of the proposed computer virus spreading model. We propose specific measures to suppress the spread of computer viruses in terminals
ensuring the safe and stable operation of the campus network terminals to the greatest extent.
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