IDEAS home Printed from https://ideas.repec.org/a/aac/ijirss/v8y2025i7p418-441id10458.html
   My bibliography  Save this article

Bio-inspired computational intelligence (BioCOIN) for cyber security during COVID-19 pandemic: A bibliometric review

Author

Listed:
  • Israel Edem Agbehadji

  • Abdultaofeek Abayomi

  • Oluwasegun Julius Aroba

  • Emmanuel Freeman

  • Richard Nana Nketsiah

Abstract

The COVID-19 pandemic profoundly disrupted the global economy, accelerating e-commerce and online activities while increasing the vulnerability of Information Technology (IT) systems. This paper aims to review the role of bio-inspired algorithms in enhancing cyber-security during the pandemic, addressing an evident research gap in this domain. A systematic review was conducted using data obtained from an online repository with broad coverage, focusing on the period 2020–2022. This timeframe captures the onset, peak, and aftermath of the pandemic. The study analyzed computational systems and applications that incorporated bio-inspired algorithms for security purposes. The review reveals that bio-inspired algorithms were already in use for cyber-security prior to the pandemic, with notable applications in Internet of Things Cyber-Physical Systems (IoT-CPS)-based Trojan detection circuits and network-layer optimization of security settings. However, the pandemic accelerated the need for resilient cyber-security frameworks and highlighted the potential of bio-inspired methods to adapt to rapidly evolving digital threats. Bio-inspired algorithms represent a valuable approach to strengthening cyber-security in times of crisis. Their adaptability and robustness make them suitable for addressing dynamic threats in increasingly interconnected ecosystems. The findings emphasize the need for continuous integration of bio-inspired approaches into cyber-security policies and infrastructures. Doing so can support more resilient digital ecosystems, enhance organizational processes, and promote better work practices in both crisis and post-crisis environments.

Suggested Citation

  • Israel Edem Agbehadji & Abdultaofeek Abayomi & Oluwasegun Julius Aroba & Emmanuel Freeman & Richard Nana Nketsiah, 2025. "Bio-inspired computational intelligence (BioCOIN) for cyber security during COVID-19 pandemic: A bibliometric review," International Journal of Innovative Research and Scientific Studies, Innovative Research Publishing, vol. 8(7), pages 418-441.
  • Handle: RePEc:aac:ijirss:v:8:y:2025:i:7:p:418-441:id:10458
    as

    Download full text from publisher

    File URL: https://ijirss.com/index.php/ijirss/article/view/10458/2480
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:aac:ijirss:v:8:y:2025:i:7:p:418-441:id:10458. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Natalie Jean (email available below). General contact details of provider: https://ijirss.com/index.php/ijirss/ .

    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.