Study On Invulnerability Based On The Community Structure Of Complex Networks

With the accelerated pace of information technology, the more closely the relationship of our lives with the network, the actual networks become increasingly complex, the increasingly close links between the nodes of the network. Accordingly, the frequency of network failure in the increase, the sheer scope of network failure is also increasing. Therefore, the complex network invulnerability is more and more the concern of scientists in various fields.This article through the complex network survivability and community structure research summary, theoretical analysis and simulation, graph theory, physics, probability and mathematical statistics, computer science and other disciplines of knowledge, research and analysis. On the one hand, propose a new survivability measure-based on the community structure of complex network invulnerability measure. Past research work the survivability measure are used on the network of global stability discussed without considering the nature of the topology of the network itself. The community structure is an important characteristic of a complex network, a network community structure is unstable, it can be said that from a certain point on the network instability. On the other hand, this paper based on the community structure of selective attacks, this attack focused on the community structure of the network, to more effectively combat network societies so that the internal collapse. In this paper, a new measure attack theory to prove and use the generated network and the actual network simulation experiments, from different angles, to prove the rationality and effectiveness of both. This article main works:the proposed measure based on the community structure of invulnerability; proposed to build a network of Shanghai Securities stock based on the community structure of selective attacks; study its invulnerability trend analysis of the shares of listed companies from the angle of invulnerability interaction between relations.