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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Measuring DoT/DoH Blocking Using OONI Probe: a Preliminary Study

S. Basso (Open Observatory of Network Interference)

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“Lose Your Phone, Lose Your Identity”: Exploring Users’ Perceptions...

Michael Lutaaya, Hala Assal, Khadija Baig, Sana Maqsood, Sonia Chiasson (Carleton University)

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A Framework for Consistent and Repeatable Controller Area Network...

Paul Agbaje (University of Texas at Arlington), Afia Anjum (University of Texas at Arlington), Arkajyoti Mitra (University of Texas at Arlington), Gedare Bloom (University of Colorado Colorado Springs) and Habeeb Olufowobi (University of Texas at Arlington)

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