Link importance assessment strategy based on improved $ k $-core decomposition in complex networks

Abstract

<abstract><p>Improving the effectiveness of target link importance assessment strategy has become an important research direction within the field of complex networks today. The reasearch shows that the link importance assessment strategy based on betweenness centrality is the current optimal solution, but its high computational complexity makes it difficult to meet the application requirements of large-scale networks. The $ k $-core decomposition method, as a theoretical tool that can effectively analyze and characterize the topological properties of complex networks and systems, has been introduced to facilitate the generation of link importance assessment strategy and, based on this, a link importance assessment indicator link shell has been developed. The strategy achieves better results in numerical simulations. In this study, we incorporated topological overlap theory to further optimize the attack effect and propose a new link importance assessment indicator link topological shell called $ t $-$ shell $. Simulations using real world networks and scale-free networks show that $ t $-$ shell $ based target link importance assessment strategies perform better than $ shell $ based strategies without increasing the computational complexity; this can provide new ideas for the study of large-scale network destruction strategies.</p></abstract>