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@article{189902,
        author = {Mohammed Manek Hossain},
        title = {A Risk-Based Cyber security Policy Model Using Artificial Intelligence},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {3420-3433},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=189902},
        abstract = {Saudi Arabia's drives rapid digital transformation across government, finance, energy, healthcare, logistics, and smart cities. This transformation increases cyber-risk exposure and pressure on regulators and organizations to adopt risk-based cybersecurity policies aligned with national frameworks. The National Cybersecurity Authority (NCA) has issued a National Cybersecurity Strategy and a draft National Framework for Cybersecurity Risk Management (NFCRM) to enable "a safe and reliable Saudi cyberspace that enables growth and prosperity." This paper proposes a conceptual Risk-Based, AI-Enabled Cybersecurity Policy Model (RAI-CPM) tailored to the Saudi context. The proposed RAI-CPM integrates four layers: (1) strategic alignment and national regulations; (2) a risk governance and policy layer; (3) an AI-driven risk analytics layer performing data collection, threat intelligence fusion, and dynamic risk scoring; and (4) an execution layer that orchestrates technical and organizational controls through risk-informed policies. The paper argues that AI-enabled risk-based cybersecurity models can (a) improve the responsiveness and proportionality of controls, (b) support measurable cyber-resilience KPIs, and (c) generate a research and innovation agenda aligned with the "digital technologies" specialization under national talent and capability initiatives.},
        keywords = {Cybersecurity, Risk-based policy, Artificial intelligence, national talent and capability initiatives, National Cybersecurity Authority, SAMA CSF, NFCRM},
        month = {January},
        }