Takami Sato (University of California, Irvine), Yuki Hayakawa (Keio University), Ryo Suzuki (Keio University), Yohsuke Shiiki (Keio University), Kentaro Yoshioka (Keio University), Qi Alfred Chen (University of California, Irvine)
ETAS Best Short Paper Award Runner-Up!
LiDAR (Light Detection And Ranging) is an indispensable sensor for precise long- and wide-range 3D sensing, which directly benefited the recent rapid deployment of autonomous driving (AD). Meanwhile, such a safety-critical application strongly motivates its security research. A recent line of research demonstrates that one can manipulate the LiDAR point cloud and fool object detection by firing malicious lasers against LiDAR. However, these efforts evaluate only a specific LiDAR (VLP-16) and do not consider the state-of-the-art defense mechanisms in the recent LiDARs, so-called next-generation LiDARs. In this WIP work, we report our recent progress in the security analysis of the next-generation LiDARs. We identify a new type of LiDAR spoofing attack applicable to a much more general and recent set of LiDARs. We find that our attack can remove >72% of points in a 10×10 m2 area and can remove real vehicles in the physical world. We also discuss our future plans.