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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FlowLens: Enabling Efficient Flow Classification for ML-based Network Security...

Diogo Barradas (INESC-ID, Instituto Superior Técnico, Universidade de Lisboa), Nuno Santos (INESC-ID, Instituto Superior Técnico, Universidade de Lisboa), Luis Rodrigues (INESC-ID, Instituto Superior Técnico, Universidade de Lisboa), Salvatore Signorello (LASIGE, Faculdade de Ciências, Universidade de Lisboa), Fernando M. V. Ramos (INESC-ID, Instituto Superior Técnico, Universidade de Lisboa), André Madeira (INESC-ID, Instituto Superior Técnico, Universidade de…

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All the Numbers are US: Large-scale Abuse of Contact...

Christoph Hagen (University of Würzburg), Christian Weinert (TU Darmstadt), Christoph Sendner (University of Würzburg), Alexandra Dmitrienko (University of Würzburg), Thomas Schneider (TU Darmstadt)

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Screen Gleaning: Receiving and Interpreting Pixels by Eavesdropping on...

Zhuoran Liu, Léo Weissbart, Dirk Lauret (Radboud University)

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The Abuser Inside Apps: Finding the Culprit Committing Mobile...

Joongyum Kim (KAIST), Jung-hwan Park (KAIST), Sooel Son (KAIST)

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