American Journal of Advanced Multidisciplinary Research and Innovation

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Cybersecurity Risk Assessment in Smart Digital Infrastructures

Author(s) Mung Chiang
Country United States
Abstract The rapid expansion of smart digital infrastructures has transformed critical sectors such as healthcare, energy, transportation, manufacturing, finance, education, telecommunications, and smart cities. These interconnected environments rely on Artificial Intelligence (AI), Internet of Things (IoT), Cloud Computing, Edge Computing, 5G/6G Networks, Blockchain Technology, Digital Twins, Big Data Analytics, Machine Learning (ML), Industrial Internet of Things (IIoT), Software-Defined Networking (SDN), Zero Trust Architecture (ZTA), Security Information and Event Management (SIEM), Extended Detection and Response (XDR), and Security Orchestration, Automation, and Response (SOAR) to deliver intelligent, automated, and data-driven services. While these technologies improve operational efficiency and digital innovation, they also expand the cyberattack surface, making systematic cybersecurity risk assessment essential for protecting critical digital assets.
This study presents a comprehensive analysis of Cybersecurity Risk Assessment in Smart Digital Infrastructures. A qualitative analytical research methodology based on secondary data is employed to examine cybersecurity risk assessment frameworks, intelligent threat detection techniques, risk mitigation strategies, governance models, and emerging security technologies. The research investigates how organisations identify, evaluate, prioritise, and manage cyber risks across complex digital ecosystems while ensuring confidentiality, integrity, availability, resilience, and regulatory compliance.
The findings indicate that AI-driven cybersecurity significantly enhances threat intelligence, anomaly detection, malware analysis, vulnerability assessment, and predictive cyber defence. Zero Trust Architecture strengthens authentication and access control by continuously verifying users, devices, and applications. Blockchain technology improves data integrity and secure identity management, while cloud-native security platforms provide scalable monitoring and automated incident response. Furthermore, digital twins enable cyber-physical risk simulation for critical infrastructure resilience.
Despite these opportunities, organisations continue to face evolving ransomware attacks, supply chain vulnerabilities, insider threats, AI-enabled cybercrime, data privacy concerns, regulatory complexity, skills shortages, and quantum computing risks. Future research should investigate autonomous cybersecurity systems, quantum-resistant cryptography, AI-driven risk modelling, adaptive Zero Trust frameworks, cyber digital twins, and privacy-preserving security analytics.
The study concludes that intelligent cybersecurity risk assessment provides a strategic foundation for securing smart digital infrastructures by integrating advanced technologies, multidisciplinary governance, continuous monitoring, and proactive risk management to support resilient and trustworthy digital transformation.
Keywords Cybersecurity Risk Assessment, Smart Digital Infrastructure, Artificial Intelligence, Zero Trust Architecture, Cloud Security, Internet of Things, Cyber Resilience, Digital Twins, Threat Intelligence, Critical Infrastructure Protection.
Field Engineering
Published In Volume 2, Issue 6, November-December 2020
Published On 2020-11-09
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