Analysis of Sensor Attacks Against Autonomous Vehicles

Abstract

Fully Autonomous Vehicles (AVs) are estimated to reach consumers widely in the near future. The manufacturers need to be completely sure that AVs can outperform human drivers, which first of all requires a solid model of the world surrounding the car. Emerging trends for perception models in the automobile industry are towards combining the data from LiDAR and camera in Multi-Sensor Fusion (MSF). Making the perception model reliable in the event of unforeseen real world circumstances is tricky enough, but the real challenge comes from the security issue that arises when ill-intentioned people try to attack sensors. We analyse possible attacks and countermeasures for LiDAR and camera. We discuss it in context of MSF, and provide a simple framework for further analysis, which we conclude will be required to conceptualise a truly safe AV.