信息工程大学学报2023，Vol.24Issue(5)：579-585,7.DOI:10.3969/j.issn.1671-0673.2023.05.011
基于多重检验特征选择的物联网设备识别
IoT Device Identification Method Based on Hypothesis Testing Feature Selection
摘要
Abstract
Accurate identification of Internet of Things(IoT)devices connected to the organization network is an effective way to maintain the organization network security.The effect of recognition tasks relying on simple features cannot be guaranteed,and systematic research on feature selection in device identification tasks is rare.To address the feature selection problem in the identification task of IoT devices,a feature selection method for IoT devices is proposed.This method uses the Kruskal-Wallis test to first select the features with differences in the overall distribution.Then the feature existence deviation extent and the inter-group deviation are quantified using the inter-group difference test method.The optimal feature subsets with inter-group deviations are screened out from multi-dimensional features by feature importance.Experiments are finally carried out on public data-sets to compare the experimental results of the optimal feature subset in common machine learning methods and feature selection methods.The experimental results verify the feasibility and effective-ness of the feature selection method for IoT devices.关键词
设备识别/特征选择/机器学习/Kruskal-Wallis检验Key words
device classification/feature selection/machine learning/Kruskal-Wallis test分类
信息技术与安全科学引用本文复制引用
石佳琪,王瑞敏,张媛媛,任化娟..基于多重检验特征选择的物联网设备识别[J].信息工程大学学报,2023,24(5):579-585,7.基金项目
国家自然科学基金青年科学基金资助项目(62002387) （62002387）
