Cybersecurity in AI-Enabled Digital Ecosystems: Evolutionary Game-Theoretic Modelling and Multi-Agent Defence

Abstract

In this era of Artifical Intelligence (AI), cyber threats are no longer static, as modern attackers are intelligent, adaptive, and capable of exploiting vulnerabilities faster than traditional defences can respond. My research investigates how attack and defence strategies co-evolve in complex, adversarial environments by integrating evolutionary game theory (EGT) with AI-driven multi-agent systems (MAS). This combined framework allows me to model strategic interactions between competing actors, analyse how defensive decisions influence overall security outcomes, and identify the conditions under which defences hold or break down. A particular focus of my work is the emergence of coordinated behaviours in multi-agent AI systems that can compromise system reliability in ways that existing safety approaches do not adequately address. Through theoretical modelling and controlled multi-agent experiments, my research proposes mechanisms that reduce attack success and strengthen defensive resilience. This work contributes to the understanding of adaptive cyber conflicts and the development of more robust and trust-worthy AI-enabled digital systems.