The AIM-PRISM Framework: A Novel Strategic Model for Machine Learning and Artificial Intelligence Deployment in National Infrastructure Cybersecurity
Year: 2025
Type: article
Abstract: The increasing intricacy and prevalence of online threats, growing complexity and frequency of cyber threats, particularly those targeting energy grids, transport systems, and financial platforms, necessitate a holistic approach to integrating intelligent technologies. This research proposes the AIM-PRISM framework, a strategic and adaptable model for deploying Artificial Intelligence (AI) and Machine Learning (ML) in cybersecurity for national infrastructure protection. While significant advancements have been made in incident response, AI-driven risk detection, and data protection, a unified deployment strategy is still lacking. Building on an extensive literature review, we identify key technological developments and implementation challenges and synthesize them into a novel eight-component framework: Adaptability, Integration, Monitoring, Predictive capacity, Responsiveness, Inclusivity, Security, and Meaningful interpretation (AIM-PRISM). This framework addresses operational, ethical, and governance considerations, offering a structured guide for policymakers, engineers, and organizational leaders. The research illustrates the framework’s application through real-world-inspired scenarios and presents criteria for evaluating AI/ML deployment readiness across infrastructure sectors.
Author: Mansoor G. Al-Thani
Institution: Ministry of Interior
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4414441222