A structured approach to anomaly detection for in-vehicle networks

Abstract

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.