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Investigation of the C-SEIRA model for controlling malicious code infection in computer networks

机译:用于控制计算机网络中恶意代码感染的C-SEIRA模型的研究

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Recently, there has been great concern about the serious burden and damage caused by malicious objects, such as computer worms, on the Internet. Therefore, the establishment of efficient policies for preventing the propagation of malicious objects becomes an important issue in the operation of computer networks. Because the propagation of malicious code is similar in many aspects to the infectious spread of biological viruses, ordinary-differential-equation-based population models, frequently used in the field of epidemiology, are useful in studying the population change of infectious hosts in computer networks. In this paper, we propose the controlled susceptible-exposed-infectious-removed-antidotal (C-SEIRA) model, an epidemiological population model describing the state transitions of a computer network under malicious code infection. For the proposed model, we derive stability results for the infection-free state and the endemic state. In addition, we apply optimal control theory to the C-SEIRA model with the goal of minimizing the infectious compartment population and the system treatment cost of isolating infectious computers from the network. Simulation results show that the spread of malicious objects can be controlled reasonably well via the optimal control approach.
机译:最近,人们非常关注Internet上由恶意对象(例如计算机蠕虫)引起的严重负担和损害。因此,建立用于防止恶意对象传播的有效策略成为计算机网络操作中的重要问题。由于恶意代码的传播在许多方面与生物病毒的传染性传播相似,因此流行病学领域中经​​常使用的基于普通差分方程的种群模型可用于研究计算机网络中感染宿主的种群变化。在本文中,我们提出了一种受控的易感性暴露传染性去除抗原(C-SEIRA)模型,这是一种流行病学人口模型,描述了恶意代码感染下计算机网络的状态转换。对于所提出的模型,我们导出了无感染状态和地方病状态的稳定性结果。此外,我们将最优控制理论应用于C-SEIRA模型,以最小化感染室的数量以及将感染计算机与网络隔离的系统处理成本。仿真结果表明,采用最优控制方法可以较好地控制恶意对象的传播。

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