IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v503y2018icp293-303.html
   My bibliography  Save this article

Global dynamics of a network-based WSIS model for mobile malware propagation over complex networks

Author

Listed:
  • Huang, Shouying

Abstract

For understanding the influence of user security awareness on the long-term spreading behavior of malware over mobile networks, in this paper, we intensively study the global dynamics of a novel network-based epidemic model with weakly-protected and strongly-protected susceptible nodes. Both analytical and numerical results show that the global dynamics of the model is completely governed by a threshold value. Specifically, we prove that when the value is lower than one, the malware-free equilibrium is globally asymptotically stable and mobile malware will disappear. When the value is greater than one, mobile malware will persist on the network, and in the meantime there exists a unique malware equilibrium which is globally asymptotically stable under certain conditions. The obtained results improve and enrich some known ones. Interestingly, increasing the recovery rate of infected nodes can result in the increase of strongly-protected susceptible nodes and the decrease of the threshold value. The study has valuable guiding significance in effectively controlling mobile malware spread.

Suggested Citation

  • Huang, Shouying, 2018. "Global dynamics of a network-based WSIS model for mobile malware propagation over complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 293-303.
    • Handle: RePEc:eee:phsmap:v:503:y:2018:i:c:p:293-303
    DOI: 10.1016/j.physa.2018.02.117
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118302127
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2018.02.117?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wei, Xiaodan & Liu, Lijun & Zhou, Wenshu, 2017. "Global stability and attractivity of a network-based SIS epidemic model with nonmonotone incidence rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 789-798.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lingyan Li & Lujiao Feng & Xiaotong Guo & Haiyan Xie & Wei Shi, 2020. "Complex Network Analysis of Transmission Mechanism for Sustainable Incentive Policies," Sustainability, MDPI, vol. 12(2), pages 1-25, January.
    2. Jose D. Hernandez Guillen & Angel Martin del Rey & Roberto Casado-Vara, 2021. "Propagation of the Malware Used in APTs Based on Dynamic Bayesian Networks," Mathematics, MDPI, vol. 9(23), pages 1-16, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Lijun & Wei, Xiaodan & Zhang, Naimin, 2019. "Global stability of a network-based SIRS epidemic model with nonmonotone incidence rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 587-599.
    2. Leyi Zheng & Longkun Tang, 2019. "A Node-Based SIRS Epidemic Model with Infective Media on Complex Networks," Complexity, Hindawi, vol. 2019, pages 1-14, February.
    3. Cheng, Xinxin & Wang, Yi & Huang, Gang, 2021. "Global dynamics of a network-based SIQS epidemic model with nonmonotone incidence rate," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:503:y:2018:i:c:p:293-303. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.