Abstract
With the rapid advance of intelligent vehicles, auxiliary driving and automatic driving have been paid more attention to. While vehicle security has become increasingly prominent, which is seriously related to the property and personal safety. The attacker can send abnormal information to the controller through internal CAN bus. Because of the particularity of the vehicle CAN network information communication protocol, the encryption authentication technology cannot effectively solve the safety problem of the vehicle network. In the paper, a novel anomaly detection method based on CAN packet content is proposed. The scheme is effective in preventing in-vehicle ECU attacks caused by malicious modifications. Statistical thinking is adopted to analyze the characteristics of normal message content. Then a confidence interval based on normal features is defined for detecting abnormal network messages. Its detection performance has been demonstrated through experiments carried out on real CAN traffic gathered from an unmodified licensed vehicle.
Our work is supported by the General Project of Tianjin Municipal Science and Technology Commission under Grant (No. 15JCYBJC15600), the Major Project of Tianjin Municipal Science and Technology Commission under Grant (No. 15ZXDSGX00030), and NSFC: The United Foundation of General Technology and Fundamental Research (No. U1536122).
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Mo, X., Chen, P., Wang, J., Wang, C. (2019). Anomaly Detection of Vehicle CAN Network Based on Message Content. In: Li, J., Liu, Z., Peng, H. (eds) Security and Privacy in New Computing Environments. SPNCE 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 284. Springer, Cham. https://doi.org/10.1007/978-3-030-21373-2_9
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DOI: https://doi.org/10.1007/978-3-030-21373-2_9
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