TY - JOUR
T1 - The Security of Autonomous Driving
T2 - Threats, Defenses, and Future Directions
AU - Ren, Kui
AU - Wang, Qian
AU - Wang, Cong
AU - Qin, Zhan
AU - Lin, Xiaodong
PY - 2020/2
Y1 - 2020/2
N2 - Autonomous vehicles (AVs) have promised to drastically improve the convenience of driving by releasing the burden of drivers and reducing traffic accidents with more precise control. With the fast development of artificial intelligence and significant advancements of the Internet of Things technologies, we have witnessed the steady progress of autonomous driving over the recent years. As promising as it is, the march of autonomous driving technologies also faces new challenges, among which security is the top concern. In this article, we give a systematic study on the security threats surrounding autonomous driving, from the angles of perception, navigation, and control. In addition to the in-depth overview of these threats, we also summarize the corresponding defense strategies. Furthermore, we discuss future research directions about the new security threats, especially those related to deep-learning-based self-driving vehicles. By 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.
AB - Autonomous vehicles (AVs) have promised to drastically improve the convenience of driving by releasing the burden of drivers and reducing traffic accidents with more precise control. With the fast development of artificial intelligence and significant advancements of the Internet of Things technologies, we have witnessed the steady progress of autonomous driving over the recent years. As promising as it is, the march of autonomous driving technologies also faces new challenges, among which security is the top concern. In this article, we give a systematic study on the security threats surrounding autonomous driving, from the angles of perception, navigation, and control. In addition to the in-depth overview of these threats, we also summarize the corresponding defense strategies. Furthermore, we discuss future research directions about the new security threats, especially those related to deep-learning-based self-driving vehicles. By 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.
KW - Autonomous vehicles
KW - Autonomous vehicles (AVs)
KW - Global Positioning System
KW - in-vehicle protocol
KW - in-vehicle systems
KW - Jamming
KW - Laser radar
KW - Security
KW - security
KW - Sensors
KW - sensors.
UR - http://www.scopus.com/inward/record.url?scp=85074614808&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85074614808&origin=recordpage
U2 - 10.1109/JPROC.2019.2948775
DO - 10.1109/JPROC.2019.2948775
M3 - RGC 21 - Publication in refereed journal
SN - 0018-9219
VL - 108
SP - 357
EP - 372
JO - Proceedings of the IEEE
JF - Proceedings of the IEEE
IS - 2
ER -