A compartmental model for global spread dynamics of malware under mutation

被引:3
|
作者
Ren, Jianguo [1 ,2 ]
Xu, Yonghong [3 ]
Xie, Chunli [1 ]
He, Shouwu [4 ]
机构
[1] Jiangsu Normal Univ, Coll Comp Sci, Xuzhou 221116, Jiangsu, Peoples R China
[2] Jiangsu Normal Univ, Res Ctr Complex Networks & Swarm Intelligence, Xuzhou, Jiangsu, Peoples R China
[3] Jiangsu Normal Univ, Key Lab Biotechnol Med Plants Jiangsu Prov, Xuzhou, Jiangsu, Peoples R China
[4] Guilin Univ Technol, Campus Nanning, Nanning, Peoples R China
基金
中国国家自然科学基金;
关键词
global stability; local stability; malware; mutation; spread modeling; COMPUTER VIRUS PROPAGATION; EPIDEMIC MODEL; STABILITY; SOFTWARE; IMPACT;
D O I
10.1002/mma.5479
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Malware mutation is pervasive among networks. Modeling and understanding its propagation characteristics have been of great importance. In this study, a new compartmental model that extends the present model by incorporating mutated malware into the modeling process as a separate dynamic variable is proposed and theoretically analyzed to deepen the understanding of the spreading mechanisms of mutated malware. The model involves two equilibria, namely, malware-free equilibrium and malware equilibrium, wherein both have proven to be locally and globally asymptotically stable through the Routh-Hurwitz criterion and Lyapunov functional approach, respectively. An epidemic threshold is obtained that clearly forms the boundary among the comprehensive dynamics of the model between two distinct ramifications: one with mutation infection prevalence and the other without any mutation infection. Both are incarnated via the existence and stability of the equilibria admitted by the model. Further analyses show that the mutation is related not only to the epidemic threshold, but also to the malware prevalence level. The numerical simulations based on the analytic results demonstrate that the diffusion of mutated malware can fall away or can be maintained at a suitable level.
引用
收藏
页码:1859 / 1869
页数:11
相关论文
共 50 条
  • [41] Development of a compartmental model describing the dynamics of vitamin A metabolism in men
    von Reinersdorff, D
    Green, MH
    Green, JB
    MATHEMATICAL MODELLING IN EXPERIMENTAL NUTRITION, 1998, 445 : 207 - 223
  • [42] Extended SEIR model of COVID-19 spread focusing on compartmental flow in England
    Li, Cheng-Ze
    Lu, Xing
    Gong, Jia-Jun
    Lei, Yu
    NONLINEAR DYNAMICS, 2025, 113 (01) : 971 - 988
  • [43] GLOBAL STABILITY ANALYSIS AND OPTIMAL PREVENTION OF COVID-19 SPREAD IN GHANA: A COMPARTMENTAL MODELLING PERSPECTIVE
    Otoo, Dominic
    Gyan, Albert
    Adusei, Hawa
    Gyamfi, Daniel
    Osman, Shaibu
    COMMUNICATIONS IN MATHEMATICAL BIOLOGY AND NEUROSCIENCE, 2023,
  • [44] Dynamic malware containment under an epidemic model with alert
    Zhang, Tianrui
    Yang, Lu-Xing
    Yang, Xiaofan
    Wu, Yingbo
    Tang, Yuan Yan
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2017, 470 : 249 - 260
  • [45] Simulation of mutation: Influence of a `side group' on global minimum structure and dynamics of a protein model
    Vekhter, Benjamin
    Berry, R. Stephen
    Journal of Chemical Physics, 111 (08):
  • [46] Simulation of mutation: Influence of a "side group" on global minimum structure and dynamics of a protein model
    Vekhter, B
    Berry, RS
    JOURNAL OF CHEMICAL PHYSICS, 1999, 111 (08): : 3753 - 3760
  • [47] Convergence to global consensus in opinion dynamics under a nonlinear voter model
    Yang, Han-Xin
    Wang, Wen-Xu
    Lai, Ying-Cheng
    Wang, Bing-Hong
    PHYSICS LETTERS A, 2012, 376 (04) : 282 - 285
  • [48] A MATHEMATICAL-MODEL FOR THE GLOBAL SPREAD OF INFLUENZA
    RVACHEV, LA
    LONGINI, IM
    MATHEMATICAL BIOSCIENCES, 1985, 75 (01) : 1 - 1
  • [49] Hajj 2016: Under the shadow of global Zika spread
    Ahmed, Qanta A.
    Kattan, Rana F.
    Memish, Ziad A.
    AMERICAN JOURNAL OF INFECTION CONTROL, 2016, 44 (12) : 1449 - 1450
  • [50] Active Nodes Maximization in a Virus Spread Model: An SI2R Malware Propagation Model
    Ngoufo, Arthur
    Kouam, Willie
    Hayel, Yezekael
    Deugoue, Gabriel
    Kamhoua, Charles
    NETWORK GAMES, ARTIFICIAL INTELLIGENCE, CONTROL AND OPTIMIZATION, NETGCOOP 2024, 2025, 15185 : 57 - 70