Dismantling Interdependent Networks Based on Supra-Laplacian Energy

Abstract

The vulnerability of complex networks is critical in the evaluation of robustness, especially attack resistance. The vulnerability of complex networks reflects the ability of network decomposition after deleting some key nodes, which is related to the collective influence maximization problem. Based on Supra-Laplacian energy, we propose a greedy algorithm (SLE) for interdependent networks to select a set of influential nodes with minimal coupling effect to maximize the collective influence. Compared with monolayer network, SLE algorithm is sensitive in interdependent networks in terms of connected component number, size of giant component, shortest distance and so on.