Deep Mining Method for Wireless Communication Network Vulnerability Based on Passive Clustering Algorithm
The types of vulnerabilities in wireless communication networks are complex,and traditional methods are difficult to accurately detect different types of vulnerabilities simultaneously.Therefore,a deep mining method for wireless communication network vulnerability based on passive clustering algorithm is proposed.This paper adopts gateway node calculation method based on passive clustering.When there is a communication demand in the network,the cluster head is set through the passive clustering algorithm,following the principle of balancing network robustness and energy efficiency to clarify the gateway nodes.It uses the clustering and filtering mechanism for abnormal gateway nodes based on information entropy to lock the abnormal gateway nodes in the network.Through a vulnerability node deep mining method based on autoregressive models,it identifies the underlying ordinary nodes within the jurisdiction of the cluster heads connected to the abnormal network nodes,combined with vulnerability judgment threshold conditions,so as to achieve deep mining in wireless communication network vulnerability.The experimental results show that this method can complete deep mining of wireless communication network vulnerability within 0.3 seconds,and the mining results are accurate.
passive clustering algorithmwireless communicationnetwork vulnerabilitydeep miningcluster head nodegateway node