The Security of Autonomous Driving: Threats, Defences, and Future
1 The Security of Autonomous Driving: Threats, Defences, and Future Directions Kui Ren, Fellow, IEEE, Qian Wang, Senior Member, IEEE, Cong Wang, Senior Member, IEEE, Zhan Qin, Member, IEEE, and Xiaodong Lin, Fellow, IEEE Abstract—Autonomous vehicles (AVs) have promised to drasti- Various Sensors cally improve the convenience of driving by releasing the burden of drivers and reducing traffic accidents with more precise Camera, Radar, LiDAR, GPS, Ultrasonic Sensor control. With the fast development of artificial intelligence and In-Vehicle Systems significant advancements of IoT technologies, we have witnessed VCS In-Vehicle Protocol the steady progress of autonomous driving over the recent years. As promising as it is, the march of autonomous driving Immobilizer CAN technologies also faces new challenges, among which security Keyless Entry LIN is the top concern. In this article, we give a systematic study on the security threats surrounding autonomous driving, from Critical Components FlexRay the angles of perception, navigation, and control. In addition to the in-depth overview of these threats, we also summarise the corresponding defence strategies. Furthermore, we discuss future research directions about the new security threats, especially those related to deep learning based self-driving vehicles. By Fig. 1: The three types of attack surfaces of an AV. providing the security guidelines at this early stage, we aim to promote new techniques and designs related to AVs from both academia and industry, and boost the development of secure autonomous driving. Recently, with the prevalence of artificial intelligence (AI) Index Terms—Autonomous Vehicles, Security, Sensors, In- and Internet of Things (IoT) technologies, autonomous driving Vehicle Systems, In-Vehicle Protocol.
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