With the rapid development of smart transportation, autonomous vehicles (AVs) are becoming one of the most anticipating means of transport. However, as the complexity of autonomous vehicles is increasing, it is intuitive that it would bring along with more possible attacks and higher potential risks. For example, by tampering the in-car sensors or hacking into any of the electronic control units (ECUs) in the vehicle, it could severely affect the driving performance or even cause life-threatening situations to users. Moreover, since AVs will also be the Internet of Vehicles (IoVs) that connect to the vehicular network in the future, the network security of the intra-vehicular and inter-vehicular links should also be carefully studied. To identify and mitigate the security risks involved in AV holistically, in this chapter, we provide a comprehensive taxonomy for attack surfaces and countermeasures for defense. Specifically, four different attack surfaces are defined, namely ECUs, sensors, intra-vehicular links, and inter-vehicular links. For each of the attack surfaces, various common attack vectors are discussed in detail. Subsequently, we also provide a survey of the latest major existing work for defending the attacks on each surface. We hope this chapter can be a guide for the general public to understand the security aspect of AVs, as well as to encourage future researchers to improve the security in AVs.
Attack Models and Countermeasures for Autonomous Vehicles
Internet of Things: Tech., Communicat., Computing
2021-06-10
27 pages
Article/Chapter (Book)
Electronic Resource
English
AUTONOMOUS VEHICLE CONTROL ATTACK DETECTION AND COUNTERMEASURES
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