基于大数据的城轨信息安全检测维护系统  

Urban Rail Information Security Detection and Maintenance System Based on Big Data

作　　者：郝菊香 冯娜[1] HAO Juxiang;FENG Na(School of Traffic and Transportation,Xi’an Traffic Engineering Institute,Xi’an 710300,China)

机构地区：[1]西安交通工程学院交通运输学院,陕西西安710300

出　　处：《微型电脑应用》2022年第4期147-148,155,共3页Microcomputer Applications

摘　　要：网络信息安全是维护轨道交通正常运行的要素之一,对此提出一种基于双轮廓的数据规则检测算法。通过引入基于专家投票的仲裁机制,融合异常检测和误用检测二者的特性,同时采用关联分析算法进行大数据隐含关系的挖掘,采取Apriori算法可有效提升检测规则的获取速度。实验结果表明,与单独的异常检测和误用检测方法相比,双轮廓检测方法对网络攻击具有更高的检测准确率。The network information security is one of the important problems for maintaining the normal operation of rail transit,hence,the data rules are proposed based on the double contour detection algorithm.By introducing arbitration mechanism based on expert voting,it fuses two features of anomaly detection and misuse detection.At the same time,it uses correlation analysis algorithm to mine large data which imply relationship,takes the Apriori algorithm to effectively improve detection rules acquisition speed.The experimental results show that compared with the single anomaly detection and misuse detection methods,the double-contour detection method has higher detection accuracy for network attacks.

关 键 词：网络安全 双轮廓 数据挖掘 大数据 规则检测 

分 类 号：TN915.08[电子电信—通信与信息系统]