IDEAS home Printed from https://ideas.repec.org/a/etm/ijsrst/v11y2024i5id969.html

Conducting IoT Vulnerability Risk Assessments in Smart Factory Networks: Tools and Techniques

Author

Listed:
  • Jeanette Uddoh
  • Daniel Ajiga
  • Babawale Patrick Okare
  • Tope David Aduloju

Abstract

In 2024, smart factories, powered by Internet of Things (IoT) devices, drive Industry 4.0, enhancing automation and efficiency but introducing significant cybersecurity risks. With 70% of smart factory networks vulnerable to IoT-related attacks, effective vulnerability risk assessments are critical to safeguard operations, data, and supply chains. This paper proposes a comprehensive framework for conducting IoT vulnerability risk assessments in smart factory networks, integrating advanced tools (e.g., Nessus, OpenVAS, Wireshark) and techniques (e.g., penetration testing, threat modeling, AI-driven analytics). Employing a mixed-method approach, the study combines a systematic literature review of 180 peer-reviewed articles and industry reports (2018–2024), tool development, and pilot testing across 10 smart factories in automotive, electronics, and pharmaceutical sectors in North America, Europe, and Asia. The proposed framework achieves 95% vulnerability detection accuracy, reduces risk exposure by 40%, and cuts assessment time by 30% compared to traditional methods. Key findings highlight the framework’s scalability across 100–10,000 IoT devices, compatibility with legacy systems, and compliance with standards like ISO 27001 and NIST 800-53. Challenges include high initial costs ($10,000–$50,000), technical complexity, and regulatory fragmentation, while opportunities involve AI-enhanced threat prediction, blockchain for auditability, and zero-trust integration. The study contributes to cybersecurity and smart manufacturing literature by offering a practical, scalable framework bridging technical, operational, and regulatory needs. For smart factory operators, it provides tools to mitigate risks, ensure compliance, and enhance resilience. Policymakers gain insights to standardize regulations, while researchers benefit from a foundation for exploring AI-driven assessments and SME-focused solutions. Future directions include quantum-resistant cryptography, automated remediation, and ethical frameworks for IoT security. By addressing these issues, this paper underscores the transformative potential of IoT vulnerability risk assessments in securing smart factory networks, fostering resilient, secure, and efficient manufacturing ecosystems.

Suggested Citation

  • Jeanette Uddoh & Daniel Ajiga & Babawale Patrick Okare & Tope David Aduloju, 2024. "Conducting IoT Vulnerability Risk Assessments in Smart Factory Networks: Tools and Techniques," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 11(5), pages 777-791, October.
  • Handle: RePEc:etm:ijsrst:v11:y2024:i5:id:969
    DOI: 10.32628/IJSRST52310379
    as

    Download full text from publisher

    File URL: https://ijsrst.com/home/article/view/IJSRST52310379
    File Function: Abstract page
    Download Restriction: no

    File URL: https://ijsrst.com/home/article/download/IJSRST52310379/IJSRST52310379
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.32628/IJSRST52310379?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
    ---><---

    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:etm:ijsrst:v11:y2024:i5:id:969. 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: Pankaj Sharma (email available below). General contact details of provider: https://ijsrst.com/home .

    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.