Agentic AI -Driven Cyber Defence Framework for Autonomous Threat Detection and Response

The increasing speed and complexity of modern cyber threats have brought into light the limitations of the traditional and human-centred processes in dealing with these threats. In this paper, we propose an innovative Cyber Defence Framework based on Agentic Artificial Intelligence (AACDF), which involves multi-agent orchestration along with autonomous decision-making abilities in the whole process of detecting and responding to threats. In particular, this framework uses dedicated agents such as perception, reasoning, action, and coordination agents working in a hierarchical manner inside the control loop based on the MAPE-K model enriched with large language model reasoning. We discuss the architecture design, the interaction mechanism between agents, and the decision-making process regarding autonomous actions for containing and remediating detected threats. A comparative analysis of the proposed framework with state-of-the-art autonomous cyber defence approaches highlights its advantages in terms of explainability and adaptability.