Gedare Bloom (University of Colorado Colorado Springs)

Best Paper Award Winner ($300 cash prize)!

The controller area network (CAN) is a high-value asset to defend and attack in automobiles. The bus-off attack exploits CAN’s fault confinement to force a victim electronic control unit (ECU) into the bus-off state, which prevents it from using the bus. Although pernicious, the bus-off attack has two distinct phases that are observable on the bus and allow the attack to be detected and prevented. In this paper we present WeepingCAN, a refinement of the bus-off attack that is stealthy and can escape detection. We evaluate WeepingCAN experimentally using realistic CAN benchmarks and find it succeeds in over 75% of attempts without exhibiting the detectable features of the original attack. We demonstrate WeepingCAN on a real vehicle.

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Physical Layer Data Manipulation Attacks on the CAN Bus

Abdullah Zubair Mohammed (Virginia Tech), Yanmao Man (University of Arizona), Ryan Gerdes (Virginia Tech), Ming Li (University of Arizona) and Z. Berkay Celik (Purdue University)

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Demo #4: Attacking Tesla Model X’s Autopilot Using Compromised...

Ben Nassi (Ben-Gurion University of the Negev), Yisroel Mirsky (Ben-Gurion University of the Negev, Georgia Tech), Dudi Nassi, Raz Ben Netanel (Ben-Gurion University of the Negev), Oleg Drokin (Independent Researcher), and Yuval Elovici (Ben-Gurion University of the Negev) Best Demo Award Winner ($300 cash prize)!

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MUVIDS: False MAVLink Injection Attack Detection in Communication for...

Seonghoon Jeong, Eunji Park, Kang Uk Seo, Jeong Do Yoo, and Huy Kang Kim (Korea University)

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