WIP: Evaluation of Threats and Impacts of HD Map Tampering Attacks in Autonomous Driving

High-definition (HD) maps are essential for autonomous vehicle (AV) navigation, providing detailed road and lane structure information. However, their static nature makes them vulnerable to tampering, posing significant security risks. This study systematically categorizes HD map tampering threats and evaluates their impact through an end-to-end autonomous driving simulation using Autoware and AWSIM. By modifying lane widths in HD maps, we demonstrate how small modifications can cause AVs to deviate from safe trajectories, affecting both planning and control. Our findings demonstrate the need for robust HD map verification, cryptographic validation of map updates, and a balance between HD map reliance and real-time perception. The study demonstrates the importance of securing HD maps to ensure safe and reliable AV operations.