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.

View More Papers

Preventing Kernel Hacks with HAKCs

Derrick McKee (Purdue University), Yianni Giannaris (MIT CSAIL), Carolina Ortega (MIT CSAIL), Howard Shrobe (MIT CSAIL), Mathias Payer (EPFL), Hamed Okhravi (MIT Lincoln Laboratory), Nathan Burow (MIT Lincoln Laboratory)

Read More

CANCloak: Deceiving Two ECUs with One Frame

Li Yue, Zheming Li, Tingting Yin, and Chao Zhang (Tsinghua University)

Read More

COOPER: Testing the Binding Code of Scripting Languages with...

Peng Xu (TCA/SKLCS, Institute of Software, Chinese Academy of Sciences; University of Chinese Academy of Sciences), Yanhao Wang (QI-ANXIN Technology Research Institute), Hong Hu (Pennsylvania State University), Purui Su (TCA/SKLCS, Institute of Software, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences)

Read More

DrawnApart: A Deep-Learning Enhanced GPU Fingerprinting Technique

Naif Mehanna (University of Lille, CNRS, Inria), Tomer Laor (Ben-Gurion University of the Negev)

Read More