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.
Anomaly detection of CAN bus messages through analysis of ID sequences / Marchetti, Mirco; Stabili, Dario. - (2017), pp. 1577-1583. (Intervento presentato al convegno 28th IEEE Intelligent Vehicles Symposium, IV 2017 tenutosi a usa nel 2017) [10.1109/IVS.2017.7995934].
Anomaly detection of CAN bus messages through analysis of ID sequences
Marchetti, Mirco
;Stabili, Dario
2017
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.
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