基于改进随机森林的物联网通信数据异常判定方法  

A Method for Anomaly Detection of Internet of Things Communication Data Based on Improved Random Forest

作　　者：班爱莹 段圆圆 BAN Aiying;DUAN Yuanyuan(School of Information and Electronic Engineering,Shangqiu Institute of Technology,Shangqiu 476000,China)

机构地区：[1]商丘工学院信息与电子工程学院,河南商丘476000

出　　处：《通信电源技术》2025年第4期153-155,共3页Telecom Power Technology

摘　　要：常规的物联网通信数据异常判定方法主要使用可扩展的面向服务的网际互连协议中间件(Scalable service-Oriented MiddlewarE over Internet Protocol,SOME/IP)协议处理通信中间件,易受交互流量异常问题影响,导致判定效果不佳。因此,提出一种基于改进随机森林的物联网通信数据异常判定方法,即使用多标签处理物联网通信异常数据,利用改进随机森林进行物联网通信数据异常判定辨识,从而实现物联网通信数据异常判定。实验结果表明,设计的物联网通信数据异常判定方法的判定效果较好,各项指标较优,具有可靠性,有一定的应用价值,为提高物联网通信质量,保证基础通信安全性做出一定的贡献。The conventional abnormal determination method of Internet of Things communication data mainly uses Scalable service-Oriented MiddlewarE over Internet Protocol(SOME/IP)protocol to process communication middleware,which is susceptible to the abnormal problem of interaction traffic and results in poor judgment effect.Therefore,an abnormal determination method of Internet of Things communication data based on improved random forest is proposed.That is,multi-label handles the abnormal data of Internet of Things communication,and the improved random forest is used to identify the abnormal data of Internet of Things communication data,so as to realize the abnormal determination of Internet of Things communication data.The experimental results show that the designed abnormal determination method of Internet of Things communication data has better judgment effect,better indicators,reliability and certain application value,which makes a certain contribution to improving the quality of Internet of Things communication and ensuring the security of basic communication.

关 键 词：改进随机森林 物联网 通信数据 异常 判定 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]