Autonomous vehicle is becoming a complex cyber-physical system with many interfaces to the external world like Wi-Fi, Bluetooth, cellular, and vehicle to anything (v2x) networks. These interfaces open new attack surfaces that can put the onboard sensors used in autonomous driving at risk of internal and external cyber-attacks that are capable of manipulating the sensor data. Since the control algorithms that define the autonomous vehicle behavior rely on the data from these onboard sensors like LiDAR, camera and RADAR, failure to secure the sensor data could lead to erroneous decisions and may result in fatal accidents. In this paper, we propose a 3D QIM based data- hiding technique to secure the raw data from LiDAR sensor. The proposed technique detects the tampering of the LiDAR sensor data and also locates the tampered region. The evaluation of the proposed method on KITTI dataset showed that the method can successfully detect and localize insider data tampering attacks such as fake target insertion (FTI) and valid target deletion (VTD).