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V.G. Dharsana Dharani is an Assistant Professor in the Department of Cyber Security at St. Joseph's College of Engineering, Chennai, India. Her research interests include cybersecurity, ethical hacking, artificial intelligence, and information security.
The swift digitalisation of essential infrastructure comprising power grids, transportation systems, healthcare networks, water utilities, telecommunications, manufacturing, and financial services has markedly heightened vulnerability to advanced cyber threats. Conventional cybersecurity methods frequently fail to identify emerging attack patterns, zero-day vulnerabilities, insider threats, and advanced persistent threats in real time. Machine Learning (ML) has arisen as a formidable tool for augmenting cybersecurity through intelligent threat detection, anomaly recognition, predictive risk evaluation, automated incident response, and adaptive defence strategies. Integrating machine learning with artificial intelligence, deep learning, cloud computing, the Industrial Internet of Things, Security Information and Event Management, and threat intelligence platforms enables organisations to enhance the resilience of critical infrastructure against cyberattacks. This chapter examines the principles, methodology, technologies, applications, difficulties, and future trajectories of machine learning in cybersecurity and critical infrastructure protection, emphasising its significance in safeguarding vital services and guaranteeing national resilience.