Robustness analysis of edge-coupled interdependent networks under different attack strategies

The robustness of interdependent networks has been a focus of research on complex networks, and the issue of attacks has become a popular research topic. However, some existing works have revealed significant vulnerabilities in interdependent networks, and the research on its robustness has been limited to node-coupled networks. While in reality, many networks are edge-coupled, and their robustness analysis has been overlooked. This paper constructs edge-coupled networks with positive, negative and random coupling based on the characteristics of edge-coupled interdependent networks. The sublayers use Erdös–Rényi (ER) random networks and scale-free (SF) networks, and four attack strategies, which includes intentional node/edge attack and random node/edge attack, are used to analyze the robustness of different edge-coupled interdependent networks. Seven edge/node importance indicators are proposed by considering node betweenness centrality, degree and eigenvector centrality, and these indicators are applied to attack strategies for result analysis, corresponding methods for enhancing robustness are proposed. The analysis results indicate that under intentional attacks, networks with negative coupling exhibit the strongest robustness, and its robustness can be influenced by their sublayers. In an environment with 500 nodes and an average degree of 4, when there is an ER network in the sublayer, protecting nodes/edges with high degree can improve the robustness of networks. If the sublayers are only composed of many SF networks, the betweenness centrality will have a greater impact when attacking most edges. While under random attacks, the networks with positive coupling exhibit the strongest robustness.