In-Vehicle Network Attack Detection Across Vehicle Models

Author:

Nakamura Shu1,Takeuchi Koh1,Kashima Hisashi1,Kishikawa Takeshi2,Haga Tomoyuki2,Sasaki Takamitsu2

Affiliation:

1. Graduate School of Informatics, Kyoto University

2. Panasonic Holdings Corporation

Publisher

Japanese Society for Artificial Intelligence

Subject

Artificial Intelligence,Software

Reference24 articles.

1. [Bhatia 14] S. Bhatia, N. Kush, C. Djamaludin, J. Akande, and E. Foo: Practical modbus flooding attack and detection, in Proceedings of the 12th Australasian Information Security Conference (AISC), pp. 57–65 (2014)

2. [Braga 10] R. Braga, E. Mota, and A. Passito: Lightweight DDoS flooding attack detection using NOX/OpenFlow, in Proceedings of the 35th IEEE Local Computer Network Conference (LCN), pp. 408–415 (2010)

3. [Breunig 00] M. M. Breunig, H.-P. Kriegel, R. T. Ng, and J. Sander: LOF: identifying density-based local outliers, in Proceedings of the ACM International Conference on Management of Data (SIGMOD), pp. 93–104 (2000)

4. [Chandola 09] V. Chandola, A. Banerjee, and V. Kumar: Anomaly detection: A survey, ACM Computing Surveys (CSUR), Vol. 41, No. 3, pp. 1–58 (2009)

5. [Cho 16] K.-T. Cho and K. G. Shin : Fingerprinting electronic control units for vehicle intrusion detection, in Proceedings of the 25th USENIX Security Symposium (USENIX Security), pp. 911–927 (2016)

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