Community-Based Robustness Analysis of Cyber-Physical Systems

This paper entails the application of the community detection problem and delves into the modularity influence on the robustness of cyber-physical systems. To illustrate this, a widely employed artificial interdependent power-communication network is adopted as a case study, examining various failure scenarios and coupling modes. The DC load flow model and generalized central betweenness model are introduced to model the power and communication network, and a strong interdependency is adopted. This approach allows visualization communities, and the impact of modularity on the interdependent network's robustness is investigated from structural and functional perspectives. Results have shown that damage to inter-community edges between different communities can lead to severe network vulnerability. Accordingly, prioritizing the security of these edges will strengthen the network's resilience, which is crucial for preventing further network damage. We also extend our analysis to examine the impact of three typical network topologies on the interdependent network's robustness, offering insights relevant to the specific network studied and applicable to other interdependent infrastructure networks.