Yunpeng Luo (UC Irvine), Ningfei Wang (UC Irvine), Bo Yu (PerceptIn), Shaoshan Liu (PerceptIn) and Qi Alfred Chen (UC Irvine)

Autonomous Driving (AD) is a rapidly developing technology and its security issues have been studied by various recent research works. With the growing interest and investment in leveraging intelligent infrastructure support for practical AD, AD system may have new opportunities to defend against existing AD attacks. In this paper, we are the first t o systematically explore such a new AD security design space leveraging emerging infrastructure-side support, which we call Infrastructure-Aided Autonomous Driving Defense (I-A2D2). We first taxonomize existing AD attacks based on infrastructure-side capabilities, and then analyze potential I-A2D2 design opportunities and requirements. We further discuss the potential design challenges for these I-A2D2 design directions to be effective in practice.

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Brian Johannesmeyer (VU Amsterdam), Jakob Koschel (VU Amsterdam), Kaveh Razavi (ETH Zurich), Herbert Bos (VU Amsterdam), Cristiano Giuffrida (VU Amsterdam)

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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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Shaik Sabiha (University at Buffalo), Keyan Guo (University at Buffalo), Foad Hajiaghajani (University at Buffalo), Chunming Qiao (University at Buffalo), Hongxin Hu (University at Buffalo) and Ziming Zhao (University at Buffalo)

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Peng Wang (Indiana University Bloomington), Zilong Lin (Indiana University Bloomington), Xiaojing Liao (Indiana University Bloomington), XiaoFeng Wang (Indiana University Bloomington)

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