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

Multi-Certificate Attacks against Proof-of-Elapsed-Time and Their Countermeasures

Huibo Wang (Baidu Security), Guoxing Chen (Shanghai Jiao Tong University), Yinqian Zhang (Southern University of Science and Technology), Zhiqiang Lin (Ohio State University)

Read More

Semantic-Informed Driver Fuzzing Without Both the Hardware Devices and...

Wenjia Zhao (Xi'an Jiaotong University and University of Minnesota), Kangjie Lu (University of Minnesota), Qiushi Wu (University of Minnesota), Yong Qi (Xi'an Jiaotong University)

Read More

MIRROR: Model Inversion for Deep Learning Network with High...

Shengwei An (Purdue University), Guanhong Tao (Purdue University), Qiuling Xu (Purdue University), Yingqi Liu (Purdue University), Guangyu Shen (Purdue University), Yuan Yao (Nanjing University), Jingwei Xu (Nanjing University), Xiangyu Zhang (Purdue University)

Read More