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Autonomous Vehicles (AVs) are mostly reliant on LiDAR sensors which enablespatial perception of their surroundings and help make driving decisions.Recent works demonstrated attacks that aim to hide objects from AV perception,which can result in severe consequences. 3D shadows, are regions void ofmeasurements in 3D point clouds which arise from occlusions of objects in ascene. 3D shadows were proposed as a physical invariant valuable for detectingspoofed or fake objects. In this work, we leverage 3D shadows to locateobstacles that are hidden from object detectors. We achieve this by searchingfor void regions and locating the obstacles that cause these shadows. Ourproposed methodology can be used to detect an object that has been hidden by anadversary as these objects, while hidden from 3D object detectors, still induceshadow artifacts in 3D point clouds, which we use for obstacle detection. Weshow that using 3D shadows for obstacle detection can achieve high accuracy inmatching shadows to their object and provide precise prediction of anobstacle's distance from the ego-vehicle.

Using 3D Shadows to Detect Object Hiding Attacks on Autonomous Vehicle Perception