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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Favocado: Fuzzing the Binding Code of JavaScript Engines Using...

Sung Ta Dinh (Arizona State University), Haehyun Cho (Arizona State University), Kyle Martin (North Carolina State University), Adam Oest (PayPal, Inc.), Kyle Zeng (Arizona State University), Alexandros Kapravelos (North Carolina State University), Gail-Joon Ahn (Arizona State University and Samsung Research), Tiffany Bao (Arizona State University), Ruoyu Wang (Arizona State University), Adam Doupe (Arizona State University),…

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Towards Understanding and Detecting Cyberbullying in Real-world Images

Nishant Vishwamitra (University at Buffalo), Hongxin Hu (University at Buffalo), Feng Luo (Clemson University), Long Cheng (Clemson University)

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Debunking Exposure Notification

Serge Vaudenay, EPFL, Switzerland

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