基于数据挖掘的城市轨道交通信息安全检测  

Information Security Detection of Urban Rail Transit Based on Data Mining

作　　者：王玮[1] 庞婷婷[1] WANG Wei;PANG Tingting(College of Traffic and Transportation, Xi’an Traffic Engineering Institute, Xi’an 710000, China)

机构地区：[1]西安交通工程学院,交通运输学院,陕西西安710000

出　　处：《微型电脑应用》2022年第2期113-115,共3页Microcomputer Applications

摘　　要：针对列车运行控制系统的通信网络安全问题,提出了一种基于数据挖掘的信息安全检测方案。以数据流为研究对象,结合轨道交通信息系统中异常数据占比少的特点,提出单分类支持向量机模型,采用超平面法,将正常数据和入侵数据进行分类,实现网络入侵行为的有效检测。仿真结果表明,在不同数据流量情况下,检测模型均能表现出较强的检测能力。Aiming at the communication network security problem of train operation control system,an information security detection scheme based on data mining is proposed.Taking the data stream as the research object,combined with the characteristics of less abnormal data in the rail transit information system,a single classification support vector machine classification model is proposed,and the hyperplane method is adopted to classify the normal data and the intrusion data,so as to realize the effective detection of network intrusion behavior.The simulation results show that the detection model has strong detection capability under different data flow conditions.

关 键 词：数据挖掘 网络安全 轨道交通 检测 支持向量机 

分 类 号：TN92[电子电信—通信与信息系统]