吉林大学学报（理学版）2018，Vol.56Issue(3)：663-668,6.DOI:10.13413/j.cnki.jdxblxb.2018.03.32
基于随机森林的车载CAN总线异常检测方法
Anomaly Detection Method for In-Vehicle CAN Bus Based on Random Forest
摘要
Abstract
Aiming at the information security problems of in-vehicle network ,on the basis of anomaly detection method of the controller area network (CAN ) bus , we proposed an anomaly detection method for CAN bus message based on the random forest model .Firstly ,a large number of normal and abnormal message data were used to construct a random forest model and perform a series of parameter adjustments .Secondly ,the CAN bus message to be detected was input into a random forest model of the corresponding ID .Finally ,a classification of the normal or abnormal message was completed by the model .The results of simulation experiment show that the model can effectively detect the abnormal data on the bus ,and improve the safety of the vehicle operation .关键词
车联网/车载CAN总线/异常检测/随机森林Key words
Internet of vehicle/in-vehicle CAN bus/anomaly detection/random forest分类
信息技术与安全科学引用本文复制引用
吴玲云,秦贵和,于赫..基于随机森林的车载CAN总线异常检测方法[J].吉林大学学报（理学版）,2018,56(3):663-668,6.基金项目
国家自然科学基金青年科学基金(批准号:61300145)和吉林省重点科技攻关项目(批准号:20150204034GX). （批准号:61300145）
