Abstract-This paper proposes a novel intrusion detection algorithm that aims to identify malicious CAN messages injected by attackers in the CAN bus of modern vehicles. The proposed algorithm identifies anomalies in the sequence of messages that flow in the CAN bus and is characterized by small memory and computational footprints, that make it applicable to current ECUs. Its detection performance are demonstrated through experiments carried out on real CAN traffic gathered from an unmodified licensed vehicle.
Marchetti et al. analyzed and identified anomalies in the sequence of CAN REF .
Anomaly detection of CAN bus messages through analysis of ID sequences
2017 IEEE Intelligent Vehicles Symposium (IV)
2017 IEEE Intelligent Vehicles Symposium (IV)
Engineering Computer Science