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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Generating 3D Adversarial Point Clouds under the Principle of...

Bo Yang (Zhejiang University), Yushi Cheng (Tsinghua University), Zizhi Jin (Zhejiang University), Xiaoyu Ji (Zhejiang University) and Wenyuan Xu (Zhejiang University)

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ScriptChecker: To Tame Third-party Script Execution With Task Capabilities

Wu Luo (Peking University), Xuhua Ding (Singapore Management University), Pengfei Wu (School of Computing, National University of Singapore), Xiaolei Zhang (Peking University), Qingni Shen (Peking University), Zhonghai Wu (Peking University)

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(Short) Spoofing Mobileye 630’s Video Camera Using a Projector

Ben Nassi, Dudi Nassi, Raz Ben Netanel and Yuval Elovici (Ben-Gurion University of the Negev)

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FedCRI: Federated Mobile Cyber-Risk Intelligence

Hossein Fereidooni (Technical University of Darmstadt), Alexandra Dmitrienko (University of Wuerzburg), Phillip Rieger (Technical University of Darmstadt), Markus Miettinen (Technical University of Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt), Felix Madlener (KOBIL)

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