As generative artificial intelligence (AI) technologies accelerate the production and spread of disinformation, traditional cybersecurity approaches prove insufficient to counter the systemic narrative threats undermining public trust and institutional stability. This paper proposes a governance-based, multi-layered policy framework for social cybersecurity called ‘Social Threat Resilience through Integrated Detection and Engagement (STRIDE)’ aimed at enhancing digital resilience against AI-driven information manipulation. Building on theoretical insights from cyber-resilience, information warfare, and inoculation theory, the STRIDE framework integrates four interdependent pillars: narrative detection, legal enforcement, public inoculation, and cross-sector coordination. Through scenario-based validation and institutional mapping, the paper demonstrates how the model aligns with contemporary regulatory instruments (e.g. the European Union’s Digital Services Act and AI Act) while addressing limitations, such as regulatory asymmetry, cognitive fatigue, and AI obsolescence. The proposed system emphasises feedback loops that adapt detection criteria based on public responses and instit
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