Biomimetic Cyber Defence Matrix - Adaptive Engagement and Swarm Intelligence For Advanced Threat Mitigation

This work explores the development of a cybersecurity architecture suitable for distributed systems which utilises swarm intelligence and adaptive threat engagement inspired by ant colonies. We propose a four-dimensional defence structure composed of Detection, Defence, Deception, and Delocalisation, and formally model the architecture around these axes by introducing corresponding effectiveness and optimality equations. We use Snort, reinforcement learning, honeypots, and Ant Colony Optimization to implement Detection, Defence, Deception, and Delocalisation respectively, exploring each in depth. We conclude that the proposed matrix, which functions as a try-catch system, is effective for the proposed use case. We implement this as a custom emulation across the four defined dimensions. Experimental results from small-scale emulation indicate that while the reinforcement learning layer exhibited instability, the integrated try-catch mechanism successfully neutralized 75\% of attack vectors, maintaining system-level integrity and availability even when individual nodes were compromised. This work demonstrates that biomimetic delocalisation and deception are critical for securing distributed environments where traditional static defenses fail.