The Spreading Dynamics of Malicious Softwares in Cyber-Physical System

doi:10.7652/xjtuxb201504013

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The Spreading Dynamics of Malicious Softwares in Cyber-Physical System

更新时间：2025-07-09

- The Spreading Dynamics of Malicious Softwares in Cyber-Physical System
- Vol. 49, Issue 4, Pages: 78-83(2015)
- 作者机构：
  
  空军工程大学信息与导航学院,西安,710077
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201504013
  CLC： TP311.5
- Online First：10 April 2015，
  
  Published：2015
- 稿件说明：
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The Spreading Dynamics of Malicious Softwares in Cyber-Physical System[J]. 2015, 49(4): 78-83.
DOI：

The Spreading Dynamics of Malicious Softwares in Cyber-Physical System[J]. 2015, 49(4): 78-83. DOI： 10.7652/xjtuxb201504013.

摘要

针对恶意软件在信息物理融合系统(cyber-physical system

CPS)中的传播机理难以描述的问题

提出了一种自适应SIQRS(susceptible-infected-quarantined-recovered-susceptible)传播动力学模型。该模型采用节点隔离机制描述CPS的感知和控制能力

引入链路重连机制刻画CPS的自适应性

进一步分析了恶意软件在CPS中的传播规则

并依据平均场理论建立了相应的微分动力学方程。不同参数条件下的仿真结果表明:当感染率小于存在阈值时

恶意软件无法在CPS内传播; 当感染率大于存在阈值且小于传播阈值时

CPS发生滞后分岔并出现双稳态现象; 当感染率大于传播阈值时

CPS稳定在地方病平衡状态; 当参数满足特定条件时

CPS会发生Hopf分岔。研究表明

所提模型能够准确刻画恶意软件在CPS中的传播机理。

Abstract

An adaptive SIQRS(susceptible-infected-quarantined-recovered-susceptible)spreading dynamics model is proposed to solve the problem that it is difficult to describe the spreading mechanism of malicious softwares in cyber-physical system(CPS). The quarantined mechanism is employed to describe the perception and control abilities of CPS

and the link rewired mechanism is introduced to depict the adaptability of CPS. The spreading rules of malicious softwares are analyzed

and their differential dynamic equations are presented based on the mean field theory. Numerical simulation results with different parameters show that when the infection rate is less than the epidemic persistence threshold

malicious softwares cannot spread in CPS; when the infection rate is larger than the epidemic persistence threshold and less than the epidemic threshold

a backward bifurcation occurs which causes the bistability; when the infection rate is larger than the epidemic threshold

CPS is stable at the endemic equilibrium; and a Hopf bifurcation occurs when the parameters satisfy a specific condition. It is concluded that the adaptive SIQRS model can accurately describe the spreading mechanism of malicious softwares in CPS.

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references

National Science Foundation of the United States. Cyber-physical system(CPS)program solicitation [EB/OL].(2013-01-14)[2014-05-29]. http:∥www.nsf.gov.

RAJKUMAR R, LEE I, SHA L. Cyber-physical systems: the next computing revolution [C]∥Proceedings of the 47th ACM/IEEE Conference on Design Automation. Piscataway, NJ, USA: IEEE, 2010: 731-736.

SAMPIGETHAYA K, POOVENDRAN R. Aviation cyber-physical systems: foundations for future aircraft and air transport [J]. Proceedings of the IEEE, 2013, 1010(8): 1834-1855.

何积丰. Cyber-physical Systems [J]. 中国计算机学会通讯, 2010, 6(1): 25-29.

HE Jifeng. Cyber-physical systems [J]. Communications of the China Computer Federation, 2010, 6(1): 25-29.

LEE I, SOKOLSKY O, CHEN Sanjian, et al. Challenges and research directions in medical cyber-physical systems [J]. Proceedings of the IEEE, 2012, 100(1): 75-90.

PASTOR-SATORRAS R, VESPIGNANI A. Epidemic spreading in scale-free networks [J]. Physical Review Letters, 2001, 86(14): 3200-3203.

BUONOMO B, RIONERO S. On the Lapunov stability for SIRS epidemic models with general nonlinear incidence rate [J]. Applied Mathematics and Computation, 2010, 217(8): 4010-4016.

TOUTONJI O A, YOO S, PARK M. Stability analysis of VEISV propagation modeling for network worm attack [J]. Applied Mathematical Modelling, 2012, 36(6): 2751-2761.

WANG Fangwei, ZHANG Yunkai, WANG Changguang, et al. Stability analysis of a SEIQV epidemic model for rapid spreading worms [J]. Computers and Security, 2010, 29(4): 410-418.

叶志勇, 刘原, 吴用. 具有非单调传染率的SIQR传染病模型的稳定性分析 [J]. 生物数学学报, 2014, 29(1): 105-112.

YE Zhiyong, LIU Yuan, WU Yong. Stability of a SIQR model with nonmonotone incidence rate [J]. Journal of Biomathematics, 2014, 29(1): 105-112.

任建国. 计算机病毒的网络传播机制: 三个新型的动力系统模型 [D]. 重庆: 重庆大学, 2012.

SHAW L B, SCHWARTZ I B. Fluctuating epidemics on adaptive networks [J]. Physical Review: E, 2008, 77(6): 248-262.

HERBERT H, MA Zhien, LIAO Shengbing. Effects of quarantine in six endemic models for infectious diseases [J]. Mathematical Bioscience, 2002, 180(1): 141-160.

鲁延玲, 蒋国平, 宋玉蓉. 自适应网络中病毒传播的稳定性和分岔行为研究 [J]. 物理学报, 2013, 62(13): 1-9.

LU Yanling, JIANG Guoping, SONG Yurong. Stability and bifurcation of epidemic spreading on adaptive network [J]. Acta Physica Sinica, 2013, 62(13): 1-9.

BARABASI A L, ALBERT R. Emergence of scaling in random networks [J]. Science, 1999, 286(5439): 509-512.

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