A structured approach to anomaly detection for in-vehicle networks
A structured approach to anomaly detection for in-vehicle networks
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DOI：
10.1109/isias.2010.5604050
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发表时间：
2010-10
期刊：
影响因子：
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通讯作者：
Michael Müter;André Groll;F. Freiling
中科院分区：
文献类型：
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作者：
Michael Müter;André Groll;F. Freiling
在过去的几年里，现代车辆的复杂性和连通性不断增加。在这一发展范围内，车载网络及其组件的安全风险大幅上升。除了对舒适性和保密性的威胁外，这些攻击还会影响车辆的安全关键系统，从而危及司机和其他道路使用者。本文讨论了在车载网络中引入异常检测系统的问题。基于典型车载网络的特点，如控制器局域网(CAN)，引入了一组异常检测传感器，允许识别车辆运行过程中的攻击，而不会导致误报。此外，还对车辆攻击检测系统的重要设计和应用准则进行了说明和讨论。
The complexity and connectivity of modern vehicles has constantly increased over the past years. Within the scope of this development the security risk for the in-vehicle network and its components has risen massively. Apart from threats for comfort and confidentiality, these attacks can also affect safety critical systems of the vehicle and therefore endanger the driver and other road users. In this paper the introduction of anomaly detection systems to the automotive in-vehicle network is discussed. Based on properties of typical vehicular networks, like the Controller Area Network (CAN), a set of anomaly detection sensors is introduced which allow the recognition of attacks during the operation of the vehicle without causing false positives. Moreover, important design and application criteria for a vehicular attack detection system are explained and discussed.