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1712991PublishedVol 6 · Issue 5

AI-Driven Supply Chain Security Framework for Healthcare IoT Ecosystems: A Zero-Trust Approach to Medical Device Vulnerability Management

Omowunmi Folashayo Makinde Nathaniel Adeniyi Akande Adetunji Oludele Adebayo Sopuluchukwu Ani Olatunde Ayomide Olasehan

Subject area: Science,Engineering and Technology  ·  Area of research: Cybersecurity

DOI: https://doi.org/10.64388/IREV6I5-1712991

Abstract

The proliferation of Internet of Things (IoT) devices in healthcare environments has fundamentally transformed patient care delivery while simultaneously introducing significant cybersecurity vulnerabilities throughout medical device supply chains. This research proposes an integrated security framework combining artificial intelligence capabilities with Zero Trust architecture principles to address critical vulnerabilities affecting medical devices from manufacturing through deployment and ongoing operations. Through comprehensive analysis of supply chain weaknesses, AI-driven detection techniques, and Zero Trust controls, this study demonstrates how these complementary approaches create defense-in-depth protecting against firmware manipulation, counterfeit components, distribution vulnerabilities, and inconsistent update mechanisms. The framework provides healthcare organizations with actionable guidance for implementing continuous monitoring, device authentication, behavioral analytics, and policy enforcement while accommodating clinical operational requirements. Recommendations address stakeholder responsibilities across hospitals, device manufacturers, and regulatory bodies to strengthen medical device security posture comprehensively.

Keywords

Healthcare IoT, Medical Device Security, Supply Chain Vulnerability, Zero Trust Architecture, Artificial Intelligence, Cybersecurity Framework, Firmware Integrity, Device Authentication

How to cite this paper

Omowunmi Folashayo Makinde, Nathaniel Adeniyi Akande, Adetunji Oludele Adebayo, Sopuluchukwu Ani, Olatunde Ayomide Olasehan "AI-Driven Supply Chain Security Framework for Healthcare IoT Ecosystems: A Zero-Trust Approach to Medical Device Vulnerability Management" Iconic Research And Engineering Journals Volume 6 Issue 5 2022 Page 300-317 https://doi.org/10.64388/IREV6I5-1712991
Omowunmi Folashayo Makinde, Nathaniel Adeniyi Akande, Adetunji Oludele Adebayo, Sopuluchukwu Ani, Olatunde Ayomide Olasehan "AI-Driven Supply Chain Security Framework for Healthcare IoT Ecosystems: A Zero-Trust Approach to Medical Device Vulnerability Management" Iconic Research And Engineering Journals, vol. 6, no. 5, Nov. 2022, doi: https://doi.org/10.64388/IREV6I5-1712991
Omowunmi Folashayo Makinde, Nathaniel Adeniyi Akande, Adetunji Oludele Adebayo, Sopuluchukwu Ani, Olatunde Ayomide Olasehan (2022). AI-Driven Supply Chain Security Framework for Healthcare IoT Ecosystems: A Zero-Trust Approach to Medical Device Vulnerability Management. Iconic Research And Engineering Journals, 6(5). doi: https://doi.org/10.64388/IREV6I5-1712991
Omowunmi Folashayo Makinde, Nathaniel Adeniyi Akande, Adetunji Oludele Adebayo, Sopuluchukwu Ani, Olatunde Ayomide Olasehan "AI-Driven Supply Chain Security Framework for Healthcare IoT Ecosystems: A Zero-Trust Approach to Medical Device Vulnerability Management" Iconic Research And Engineering Journals, vol. 6, no. 5, Nov. 2022. Crossref, https://doi.org/10.64388/IREV6I5-1712991
@article{1712991,
      author = {Omowunmi Folashayo Makinde, Nathaniel Adeniyi Akande, Adetunji Oludele Adebayo, Sopuluchukwu Ani, Olatunde Ayomide Olasehan},
      title = {AI-Driven Supply Chain Security Framework for Healthcare IoT Ecosystems: A Zero-Trust Approach to Medical Device Vulnerability Management},
      journal = {Iconic Research And Engineering Journals},
      year = {2022},
      volume = {6},
      number = {5},
      pages = {300-317},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1712991.pdf},
      abstract = {The proliferation of Internet of Things (IoT) devices in healthcare environments has fundamentally transformed patient care delivery while simultaneously introducing significant cybersecurity vulnerabilities throughout medical device supply chains. This research proposes an integrated security framework combining artificial intelligence capabilities with Zero Trust architecture principles to address critical vulnerabilities affecting medical devices from manufacturing through deployment and ongoing operations. Through comprehensive analysis of supply chain weaknesses, AI-driven detection techniques, and Zero Trust controls, this study demonstrates how these complementary approaches create defense-in-depth protecting against firmware manipulation, counterfeit components, distribution vulnerabilities, and inconsistent update mechanisms. The framework provides healthcare organizations with actionable guidance for implementing continuous monitoring, device authentication, behavioral analytics, and policy enforcement while accommodating clinical operational requirements. Recommendations address stakeholder responsibilities across hospitals, device manufacturers, and regulatory bodies to strengthen medical device security posture comprehensively.},
      keywords = {Healthcare IoT, Medical Device Security, Supply Chain Vulnerability, Zero Trust Architecture, Artificial Intelligence, Cybersecurity Framework, Firmware Integrity, Device Authentication},
      month = {November},
      doi = {https://doi.org/10.64388/IREV6I5-1712991}
  }