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基于CAN的现代车辆入侵检测

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现代汽车广泛使用CAN总线结构控制车辆内的各种电子部件,但标准的CAN协议存在漏洞,易受到拒绝服务、模糊攻击和重放等攻击,而传统的基于IP协议的入侵检测技术不能直接应用于现代车辆。于是分析CAN结构,找到其缺陷;针对CAN的攻击技术,分析CAN总线特征后,融合基于频率检测、机器学习和统计检测三种异常检测方法对车辆进行入侵检测,通过实验验证,可以总体上提高现代车辆入侵检测系统的性能。
MODERN VEHICLE INTRUSION DETECTION BASED ON CAN
Modern vehicles widely use controller area network(CAN)bus structure to control various electronic components in vehicles,but the standard CAN protocol lacks defense mechanism and is vulnerable to be attacked such as denial of service,fuzzy attack and replay.Traditional intrusion detection technology based on IP protocol can't be directly applied in modern vehicles.The CAN structure was analyzed to find its defects.Aimed at CAN attack technology,after analyzing the CAN bus features,three anomaly detection methods based on frequency detection,machine learning and statistical detection were fused to detect vehicle intrusion detection.Through experimental verification,the performance of modern vehicle intrusion detection system is improved in general by the proposed method.

CANIntrusion detectionFrequency detectionMachine learningStatistical detection

赵丽、孙敏

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晋中学院信息技术与工程系 山西 晋中 030619

山西大学计算机与信息技术学院 山西 太原 030006

CAN 入侵检测 频率检测 机器学习 统计检测

山西省高等学校教学改革创新项目晋中学院"1331 工程"创客团队项目

J2020314jzxycktd2019029

2024

计算机应用与软件
上海市计算技术研究所 上海计算机软件技术开发中心

计算机应用与软件

CSTPCD北大核心
影响因子:0.615
ISSN:1000-386X
年,卷(期):2024.41(2)
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