Study on Network Vulnerability Identification and Equilibrated Network Immunization Strategy

Abstract

SUMMARYNetwork structure has a great impact both on hazard spread and network immunization. The vulnerability of the network node is associated with each other, assortative or disassortative. Firstly, an algorithm for vulnerability relevance clustering is proposed to show that the vulnerability community phenomenon is obviously existent in complex networks. On this basis, next, a new indicator called network "hyperbetweenness" is given for evaluating the vulnerability of network node. Network hyper-betweenness can reflect the importance of network node in hazard spread better. Finally, the dynamic stochastic process of hazard spread is simulated based on Monte-Carlo sampling method and a twoplayer, non-cooperative, constant-sum game model is designed to obtain an equilibrated network immunization strategy. key words: network vulnerability community, hyper-betweenness, network immunization strategy, matrix game model, complex networks

An Efficient Network Immunization Strategy with Network Embedding

“…Betweenness-based strategy will block the nodes which is important in the view of whole network. The importance of immunized nodes can be evaluated by several metrics, shortest distance [11], DIL-rank [12], k-core [5,13], eigenvector centrality [14], hyper-betweenness [15]. These methods face a common problem, with the growth of network size, it will be difficult to calculate the importance of the nodes over complete network structure.…”