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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KUBO: Precise and Scalable Detection of User-triggerable Undefined Behavior...

Changming Liu (Northeastern University), Yaohui Chen (Facebook Inc.), Long Lu (Northeastern University)

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C^2SR: Cybercrime Scene Reconstruction for Post-mortem Forensic Analysis

Yonghwi Kwon (University of Virginia), Weihang Wang (University at Buffalo, SUNY), Jinho Jung (Georgia Institute of Technology), Kyu Hyung Lee (University of Georgia), Roberto Perdisci (Georgia Institute of Technology and University of Georgia)

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Effects of Precise and Imprecise Value-Set Analysis (VSA) Information...

Laura Matzen, Michelle A Leger, Geoffrey Reedy (Sandia National Laboratories)

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