  Critical National Infrastructure (CNI) encompasses a nation's essential
assets that are fundamental to the operation of society and the economy,
ensuring the provision of vital utilities such as energy, water,
transportation, and communication. Nevertheless, growing cybersecurity threats
targeting these infrastructures can potentially interfere with operations and
seriously risk national security and public safety. In this paper, we examine
the intricate issues raised by cybersecurity risks to vital infrastructure,
highlighting these systems' vulnerability to different types of cyberattacks.
We analyse the significance of trust, privacy, and resilience for Critical
Infrastructure Protection (CIP), examining the diverse standards and
regulations to manage these domains. We also scrutinise the co-analysis of
safety and security, offering innovative approaches for their integration and
emphasising the interdependence between these fields. Furthermore, we introduce
a comprehensive method for CIP leveraging Generative AI and Large Language
Models (LLMs), giving a tailored lifecycle and discussing specific applications
across different critical infrastructure sectors. Lastly, we discuss potential
future directions that promise to enhance the security and resilience of
critical infrastructures. This paper proposes innovative strategies for CIP
from evolving attacks and enhances comprehension of cybersecurity concerns
related to critical infrastructure.
