基于物联网的通信网络异常节点检测方法研究

Research on Detection Method of Abnormal Nodes in Communication Network Based on Internet of Things

通信网络受自身链路与人为操作的影响,会出现程度不同的网络异常节点,影响网络的使用安全。传统通信网络异常节点检测为全局扫描检测,由于检测过程过于单一,导致检测漏报率偏高。因此,研究基于物联网的通信网络异常节点检测方法尤为必要。该方法利用物联网信息交互、统筹全局的能力,定位通信网络异常范围;通过提取异常节点特征,构建具有循环检测功能的检测模型;通过压缩感知异常节点信息,实现对异常节点的检测。结果表明:与传统检测方法相比,此次研究的检测方法可以检测出属性不同的异常节点,降低了检测漏报率。

The communication network is affected by its own links and human operations,and abnormal network nodes of different degrees will appear,which affects the safety of the network.The traditional detection method of abnormal nodes in communication network is global scanning detection.Due to the single detection process,the detection rate is high.Therefore,it is necessary to study the abnormal node detection method based on Internet of things.This method uses the ability of information interaction and overall planning of the Internet of things to locate the abnormal range of communication network;by extracting the characteristics of abnormal nodes,a detection model with cyclic detection function is constructed;and the abnormal node detection is realized by compressing and sensing the abnormal node information.The results show that:compared with the traditional detection methods,the detection method of this study can detect abnormal nodes with different attributes,and reduce the rate of false negative detection.