Optimal Dismantling of Interdependent Networks Based on Inverse Explosive Percolation

Seeking nodes whose removal can effectively dismantle networks is closely related to the robustness of networks under targeted attacks or malicious software. Modern systems, such as critical infrastructure networks and cyber-physical systems, however, become increasingly dependent on others, which can be encapsulated into the framework of interdependent networks. In this brief, we focus on the optimal dismantling of interdependent networks, and propose a novel algorithm, named inverse explosive percolation (IEP), to find the optimal removal nodes. The IEP proceeds by first identifying the nodes which make the least contribution to the giant mutual connected cluster of interdependent networks. When nodes have the same contribution, the one with the smallest overlapping degree is selected. We apply the IEP algorithm to interdependent networks composed of real-world power grids, Internet networks and artificial networks, and find IEP performs much better than the existing methods in various kinds of networks. Based on its efficiency, IEP can be applied to large-scale systems.