Feasibility study on anomaly detection in multi-LiDAR sensor network

Light-detection-and-ranging (LiDAR) sensors are essential for the automated operation of network-connected vehicles in smart cities but are vulnerable to cyber-attacks. This paper introduces a system for anomaly detection that verifies the consistency of point cloud data across multiple LiDAR sensors. By comparing metrics derived from point cloud distributions under normal and potentially compromised conditions, the system effectively identifies anomalies, enhancing the security and reliability of network-connected LiDAR systems.