Vulnerability analysis of power communication network based on complex network theory

Aiming at the problems of insufficient recognition ability and inaccurate recognition results of traditional communication network weak area identification methods, this paper proposes a communication network weak link identification algorithm based on community influence. Firstly, the community structure of the network is discovered by the community discovery algorithm GN algorithm, which can divide the network into multiple communities; secondly, the communication network weakness assessment index is constructed from two aspects of community local influence and community global influence; finally, the method proposed in this paper is verified and analyzed by the actual power communication network. The simulation results show that the weak link identification algorithm of power communication network proposed in this paper has higher discriminability and accuracy compared with traditional methods.