Artificial Intelligence-Driven Cybersecurity for Critical Infrastructure Protection: A Pathway to Sustainable Development

Abstract

The increasing digitalization of critical infrastructure sectors such as energy, healthcare, transportation, finance, and industrial systems has significantly expanded their exposure to cyber threats. Traditional cybersecurity approaches are increasingly challenged by sophisticated attacks that exploit interconnected digital environments. This study examines the role of Artificial Intelligence (AI)-driven cybersecurity in protecting critical infrastructure and supporting sustainable development. Using a systematic qualitative literature review, the study synthesizes evidence from peer-reviewed research published between 2018 and 2025 on AI applications in cybersecurity, cyber resilience, and critical infrastructure protection. The findings indicate that AI technologies, particularly Machine Learning (ML) and Deep Learning (DL), significantly improve threat detection accuracy, reduce incident response times, and enable predictive security capabilities. AI-driven solutions have demonstrated effectiveness across multiple critical infrastructure sectors by supporting real-time anomaly detection, automated response mechanisms, and proactive threat mitigation. These capabilities strengthen cyber resilience and contribute to sustainable development objectives through enhanced infrastructure reliability, secure digital services, and institutional stability. However, the study identifies several challenges, including adversarial attacks against AI systems, data quality limitations, lack of explainability, skills shortages, and inadequate regulatory frameworks. The research argues that the successful adoption of AI-driven cybersecurity requires trustworthy, explainable, and well-governed systems supported by appropriate policies, ethical frameworks, and capacity-building initiatives. The study concludes that AI-driven cybersecurity represents a critical pathway for safeguarding critical infrastructure and advancing sustainable development, provided that implementation balances technological innovation with transparency, accountability, and human oversight.