Stochastic Game for Collaborative Defense in Multi-domain Networks: A MAPPO Approach

As cross-domain access constitutes a significant portion of network communication, multi-domain networks present both enhanced capabilities and increased cybersecurity risks. Traditional defense strategies often overlook the complexities of cross-domain collaboration, particularly the strategic interactions among domains that prioritize their own interests. In this paper, we introduce Macd, a multi-domain collaborative defense framework, which models the defense interactions as a multi-agent stochastic game. This enables Macd to consider long-term security performance across domains, mitigating multi-step attack threats. To promote effective collaboration, we propose a Shapley-value based reputation mechanism to ensure fair incentives for non-attacked domains that contributing Security Service Functions (SSFs). Additionally, we implement a MAPPO-based Macd-solver to dynamically compute optimal defense strategies. Simulations in a DDoS attack-defense scenario demonstrate that Macd significantly enhances cross-domain collaboration and improves the overall security of multi-domain networks.