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May 31, 20260 citationsOpen Access

AI-Driven Cybersecurity Governance Framework for Critical Infrastructure Protection: Integrating Zero Trust, Digital Resilience, and Institutional Preparedness for Adaptive Cyber Defense

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VJVincent Chinedu JohnsonEuropean School of Management and Technology

Key Points

  • The research aims to create a comprehensive AI-driven cybersecurity governance framework to enhance protection for critical infrastructure.
  • Development of a seven-layer governance model based on established cybersecurity frameworks.
  • Integration of AI, Zero Trust, cyber risk scoring, and resilience planning.
  • Analysis of critical asset protection and executive oversight mechanisms.
  • Introduced the Cyber Risk Score (CRS) model to prioritize cyber risks.
  • Demonstrated the necessity of integrating governance with technical cybersecurity practices.
  • Validated the framework's applicability in both developed and developing economies.

Abstract

EXECUTIVE SUMMARY Critical infrastructure sectors—including energy, healthcare, transportation, telecommunications, finance, water systems, and government services—are increasingly dependent on interconnected digital technologies. While these technologies improve efficiency, innovation, and service delivery, they simultaneously expand the attack surface available to cyber adversaries. This study proposes an AI-Driven Cybersecurity Governance Framework for Critical Infrastructure Protection that integrates Artificial Intelligence (AI), Zero Trust governance, cyber risk scoring, operational resilience, and institutional preparedness into a unified governance architecture. The framework addresses a persistent challenge within cybersecurity practice: the disconnect between technical threat detection and governance-level cyber risk decision-making. Drawing upon established cybersecurity frameworks including NIST Cybersecurity Framework 2.0, NIST Zero Trust Architecture, ISO/IEC 27001:2022, ENISA guidance, and CISA Cybersecurity Performance Goals, the study develops a seven-layer governance model that supports critical asset protection, AI-assisted threat detection, resilience planning, executive oversight, and continuous improvement. The proposed Cyber Risk Score (CRS) model further enables organizations to prioritize cyber risks according to threat probability, asset criticality, exposure severity, business impact, and recovery readiness. The framework contributes to cybersecurity governance research by providing a practical and scalable approach suitable for both developed and developing economies. It emphasizes that effective cybersecurity is no longer solely a technical challenge but a governance, resilience, and institutional preparedness challenge requiring coordinated leadership across technical, operational, and executive domains. Keywords: Cybersecurity Governance, Artificial Intelligence, Critical Infrastructure Protection, Digital Resilience, Zero Trust, Cyber Risk Management, Institutional Preparedness, Cyber Resilience.

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Vincent Chinedu Johnson (2026) studied this question.

synapsesocial.com/papers/6a1bd2515783ba022b6fdb32https://doi.org/10.5281/zenodo.20446326
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