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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ATTEQ-NN: Attention-based QoE-aware Evasive Backdoor Attacks

Xueluan Gong (Wuhan University), Yanjiao Chen (Zhejiang University), Jianshuo Dong (Wuhan University), Qian Wang (Wuhan University)

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VISAS-Detecting GPS spoofing attacks against drones by analyzing camera's...

Barak Davidovich (Ben-Gurion University of the Negev), Ben Nassi (Ben-Gurion University of the Negev) and Yuval Elovici (Ben-Gurion University of the Negev)

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DRAWN APART: A Device Identification Technique based on Remote...

Tomer Laor (Ben-Gurion Univ. of the Negev), Naif Mehanna (Univ. Lille, CNRS, Inria), Antonin Durey (Univ. Lille, CNRS, Inria), Vitaly Dyadyuk (Ben-Gurion Univ. of the Negev), Pierre Laperdrix (Univ. Lille, CNRS, Inria), Clémentine Maurice (Univ. Lille, CNRS, Inria), Yossi Oren (Ben-Gurion Univ. of the Negev), Romain Rouvoy (Univ. Lille, CNRS, Inria / IUF), Walter Rudametkin…

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