Imperial College London
Portrait Picture

DrSoterisDemetriou

Faculty of Engineering, Department of Computing

Lecturer
 
 
 
//

Contact

 

+44 (0)20 7594 8237s.demetriou Website CV

 
 
//

Assistant

 

Ms Lucy Atthis +44 (0)20 7594 8259

 
//

Location

 

353ACE ExtensionSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@inproceedings{Hau:2021,
author = {Hau, Z and Co, KT and Demetriou, S and Lupu, E},
publisher = {Internet Society},
title = {Object removal attacks on LiDAR-based 3D object detectors},
url = {https://www.ndss-symposium.org/ndss-paper/auto-draft-112/},
year = {2021}
}
Download

RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - 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.
AU  - Hau,Z
AU  - Co,KT
AU  - Demetriou,S
AU  - Lupu,E
PB  - Internet Society
PY  - 2021///
TI  - Object removal attacks on LiDAR-based 3D object detectors
UR  - https://www.ndss-symposium.org/ndss-paper/auto-draft-112/
UR  - http://hdl.handle.net/10044/1/87736
ER  -
Download