Introduction Cognitive cities integrate autonomous decision-making, machine learning, and Internet of Things networks to create adaptive urban environments. These technologies introduce cybersecurity challenges that existing enterprise and smart city frameworks do not adequately address. This study develops an evidence-based readiness model to assess and advance cybersecurity preparedness in cognitive cities. Methods A three-phase methodology develops the model. Phase 1 elicits cybersecurity best practices through a focused review mapped to documented cognitive city security challenges, Phase 2 organizes the practices into knowledge areas and readiness levels, and Phase 3 evaluates the result through a panel of ten cybersecurity experts and an initial application case study in a large-scale real-world cognitive city. Results The resulting Cognitive City Cybersecurity Readiness Index (C3RI) comprises 117 best practices organized into eight Cybersecurity Knowledge Areas and distributed across five progressive readiness levels (Foundational, Structured, Intelligent, Autonomous, and Adaptive). A Motorola-based assessment scores each practice across Approach, Deployment, and Results, and a 7.0 advancement gate governs progression between levels. In the case study, level means range from 7.04 to 7.52 and exceed the gate at every readiness level. The expert review supports the clarity, coverage, and practical applicability of the model.
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Alshareef et al. (2026) studied this question.
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