基于RF-RFECV和LightGBM的物联网僵尸网络检测模型研究与实现  

RESEARCH AND IMPLEMENTATION OF IOT BOTNET DETECTION MODEL BASED ON RF-RFECV AND LIGHTGBM

作　　者：胡晋宁 莫秀良 Hu Jinning;Mo Xiuliang(School of Computer Science and Engineering,Tianjin University of Technology,Tianjin 300384,China;Tianjin Key Laboratory of Intelligent Computing and New Software Technology,Tianjin 300384,China)

机构地区：[1]天津理工大学计算机科学与工程学院,天津300384 [2]天津市智能计算及软件新技术重点实验室,天津300384

出　　处：《计算机应用与软件》2025年第4期340-344,388,共6页Computer Applications and Software

基　　金：天津市科委面上项目(15JCYBJC15600);天津市科委重大专项(15ZXDSGX00030)。

摘　　要：日常的物联网设备普遍存在安全等级较低的情况,这会产生许多潜在的安全性问题,物联网僵尸网络就是其中之一。针对上述问题,提出一种基于RF-RFECV和LightGBM的物联网僵尸网络检测模型,该模型采用RF-RFECV根据特征重要性进行特征选择,并使用LightGBM构建模型。实验结果表明,该模型在准确率、精确率、召回率和F1分数上与传统的检测模型相比均有一定程度的提升,这对于今后研究物联网僵尸网络的检测具有积极的推进作用。The security level of Internet of Things devices is generally low,which has caused many hidden safety hazards.The IoT botnet is one of them.In response to the above problems,an IoT botnet detection model based on RF-RFECV and LightGBM is designed.The model used RF-RFECV to select features according to the importance of features,and used LightGBM to build the model.The experimental results show that this model is improved to a certain extent compared with the traditional detection algorithm in accuracy,precision,recall rate and F1 score,which is useful for future IoT botnet research.

关 键 词：物联网 僵尸网络 Mirai LightGBM 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]