Hyunjae Kang, Byung Il Kwak, Young Hun Lee, Haneol Lee, Hwejae Lee, and Huy Kang Kim (Korea University)

Cybersecurity competitions can promote the importance of security and discover talented researchers. We hosted the Car Hacking: Attack & Defense Challenge from September 14, 2020 to November 27, 2020, and many security companies and researchers participated. To the best of our knowledge, it is the first competition to contest both attack and detection techniques on an in-vehicle network, specifically Controller Area Network (CAN). The participants developed various injection attacks and high-performance detection algorithms based on the real vehicle environment. Rule-based and ensemble tree-based models dominated the final round. Also, time interval and data byte patterns worked as major features to detect attacks.

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Demo #10: Security of Deep Learning based Automated Lane...

Takami Sato, Junjie Shen, Ningfei Wang (UC Irvine), Yunhan Jia (ByteDance), Xue Lin (Northeastern University), and Qi Alfred Chen (UC Irvine)

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A Framework for Consistent and Repeatable Controller Area Network...

Paul Agbaje (University of Texas at Arlington), Afia Anjum (University of Texas at Arlington), Arkajyoti Mitra (University of Texas at Arlington), Gedare Bloom (University of Colorado Colorado Springs) and Habeeb Olufowobi (University of Texas at Arlington)

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Detecting CAN Masquerade Attacks with Signal Clustering Similarity

Pablo Moriano (Oak Ridge National Laboratory), Robert A. Bridges (Oak Ridge National Laboratory) and Michael D. Iannacone (Oak Ridge National Laboratory)

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WeepingCAN: A Stealthy CAN Bus-off Attack

Gedare Bloom (University of Colorado Colorado Springs) Best Paper Award Winner ($300 cash prize)!

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