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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PHYjacking: Physical Input Hijacking for Zero-Permission Authorization Attacks on...

Xianbo Wang (The Chinese University of Hong Kong), Shangcheng Shi (The Chinese University of Hong Kong), Yikang Chen (The Chinese University of Hong Kong), Wing Cheong Lau (The Chinese University of Hong Kong)

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Building the VPNalyzer System

Reethika Ramesh (University of Michigan), Leonid Evdokimov (Independent), Diwen Xue, Roya Ensafi (University of Michigan)

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Demo #10: Hijacking Connected Vehicle Alexa Skills

Wenbo Ding (University at Buffalo), Long Cheng (Clemson University), Xianghang Mi (University of Science and Technology of China), Ziming Zhao (University at Buffalo) and Hongxin Hu (University at Buffalo)

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