Zhongyuan Hau, Kenneth Co, Soteris Demetriou, and Emil Lupu (Imperial College London)

Best Short Paper Award Runner-up!

LiDARs play a critical role in Autonomous Vehicles’ (AVs) perception and their safe operations. Recent works have demonstrated that it is possible to spoof LiDAR return signals to elicit fake objects. In this work we demonstrate how the same physical capabilities can be used to mount a new, even more dangerous class of attacks, namely Object Removal Attacks (ORAs). ORAs aim to force 3D object detectors to fail. We leverage the default setting of LiDARs that record a single return signal per direction to perturb point clouds in the region of interest (RoI) of 3D objects. By injecting illegitimate points behind the target object, we effectively shift points away from the target objects’ RoIs. Our initial results using a simple random point selection strategy show that the attack is effective in degrading the performance of commonly used 3D object detection models.

View More Papers

Reining in the Web's Inconsistencies with Site Policy

Stefano Calzavara (Università Ca' Foscari Venezia), Tobias Urban (Institute for Internet Security and Ruhr University Bochum), Dennis Tatang (Ruhr University Bochum), Marius Steffens (CISPA Helmholtz Center for Information Security), Ben Stock (CISPA Helmholtz Center for Information Security)

Read More

User Expectations and Understanding of Encrypted DNS Settings

Alexandra Nisenoff, Nick Feamster, Madeleine A Hoofnagle†, Sydney Zink. (University of Chicago and †Northwestern)

Read More

Flexsealing BGP Against Route Leaks: Peerlock Active Measurement and...

Tyler McDaniel (University of Tennessee, Knoxville), Jared M. Smith (University of Tennessee, Knoxville), Max Schuchard (University of Tennessee, Knoxville)

Read More

Detecting CAN Masquerade Attacks with Signal Clustering Similarity

Pablo Moriano (Oak Ridge National Laboratory), Robert A. Bridges (Oak Ridge National Laboratory) and Michael D. Iannacone (Oak Ridge National Laboratory)

Read More