The Role of Artificial Intelligence-Driven Big Data Analytics in Strengthening Cybersecurity Frameworks for Critical Infrastructure

Abstract

The rapid digital transformation across sectors has elevated the significance of robust cybersecurity frameworks, particularly for critical infrastructure systems. These systems—spanning energy grids, financial networks, healthcare facilities, and transportation—are increasingly interconnected, making them prime targets for sophisticated cyber threats. Traditional cybersecurity solutions are often inadequate in the face of rapidly evolving threats. Artificial Intelligence (AI)-driven big data analytics (BDA) offers a transformative approach to fortifying cybersecurity frameworks by enabling real-time threat detection, predictive analysis, and automated response mechanisms. AI-driven BDA leverages the power of machine learning (ML), natural language processing (NLP), and deep learning to process vast amounts of data, identify anomalies, and respond to potential threats with precision. This paper explores the integration of AI and BDA in cybersecurity, emphasizing its role in critical infrastructure protection. The discussion highlights key benefits, challenges, and implementation strategies. By examining real-world applications, this study underscores the transformative potential of AI-driven BDA in enhancing cybersecurity resilience, fostering proactive defense mechanisms, and ensuring the integrity of vital systems.