Yulong Cao, Jiaxiang Ma, Kevin Fu (University of Michigan), Sara Rampazzi (University of Florida), and Z. Morley Mao (University of Michigan)

Best Demo Award Runner-up ($200 cash prize)!

Recent studies have demonstrated that LiDAR sensors are vulnerable to spoofing attacks, in which adversaries spoof fake points to fool the car’s perception system to see nonexistent obstacles. However, these attacks are generally conducted on static or simulated scenarios. Therefore, in this demo, we perform the first LiDAR spoofing attack on moving targets. We implemented a minimal tracking system integrated with the spoofer device to perform laser-based attacks on Lidar sensors. The demo shows how it is possible to inject up to 100 fake cloud points under three different scenarios.

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Zhisheng Hu (Baidu), Shengjian Guo (Baidu) and Kang Li (Baidu)

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POP and PUSH: Demystifying and Defending against (Mach) Port-oriented...

Min Zheng (Orion Security Lab, Alibaba Group), Xiaolong Bai (Orion Security Lab, Alibaba Group), Yajin Zhou (Zhejiang University), Chao Zhang (Institute for Network Science and Cyberspace, Tsinghua University), Fuping Qu (Orion Security Lab, Alibaba Group)

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WINNIE : Fuzzing Windows Applications with Harness Synthesis and...

Jinho Jung (Georgia Institute of Technology), Stephen Tong (Georgia Institute of Technology), Hong Hu (Pennsylvania State University), Jungwon Lim (Georgia Institute of Technology), Yonghwi Jin (Georgia Institute of Technology), Taesoo Kim (Georgia Institute of Technology)

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Demo #8: Security of Camera-based Perception for Autonomous Driving...

Christopher DiPalma, Ningfei Wang, Takami Sato, and Qi Alfred Chen (UC Irvine)

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