WIP: Towards Practical LiDAR Spoofing Attack against Vehicles Driving at Cruising Speeds
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Presented at NDSS Symposium 2024 by
LiDAR (Light Detection and Ranging) is an essential sensor for autonomous driving (AD), increasingly being integrated not only in prototype vehicles but also in commodity vehicles. Due to its critical safety implications, recent studies have explored its security risks and exposed the potential vulnerability against LiDAR spoofing attacks, which manipulate measurement data by emitting malicious lasers into the LiDAR. Nevertheless, deploying LiDAR spoofing attacks against driving AD vehicles still has significant technical challenges particularly in accurately aiming at the LiDAR of a moving AV from the roadside. The current state-of-the-art attack can be successful only at ≤5 km/h. Motivated by this, we design novel tracking and aiming methodology and conduct a feasibility study to explore the actual practicality of LiDAR spoofing attacks against AD vehicles at cruising speeds. In this work, we report our initial results demonstrating that our object removal attack successfully makes the targeted pedestrian undetectable with ≥90% success rates in a real-world scenario where the adversary at the roadside attacks the victim AD approaching at 35 km/h. Finally, we discuss the current challenges and our future plans.