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Intelligent Technologies for Internet of Vehicles pp 375–401Cite as

Attack Models and Countermeasures for Autonomous Vehicles

Part of the Internet of Things book series (ITTCC)

Abstract

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.

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Acknowledgements

This research is supported by A*STAR under its RIE2020 Advanced Manufacturing and Engineering (AME) Industry Alignment Fund – Pre-Positioning (IAF-PP), Singapore (Grant No. A19D6a0053).

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Authors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Man Chun Chow, Maode Ma & Zhijin Pan

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  1. Man Chun Chow
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  2. Maode Ma
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Correspondence to Maode Ma .

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Editors and Affiliations

  1. LASIGE, Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal

    Naercio Magaia

  2. Department of Management Science and Technology, Hellenic Mediterranean University, Agios Nikolaos, Lakonia, Greece

    Dr. George Mastorakis

  3. Department Computer Science, University of Nicosia, Nicosia, Cyprus

    Prof. Dr. Constandinos Mavromoustakis

  4. Department of Electrical and Computer Engineering, Hellenic Mediterranean University, Heraklion, Greece

    Prof. Evangelos Pallis

  5. Department of Electrical and Computer Engineering, Hellenic Mediterranean University, Heraklion, Greece

    Evangelos K. Markakis

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Chow, M.C., Ma, M., Pan, Z. (2021). Attack Models and Countermeasures for Autonomous Vehicles. In: Magaia, N., Mastorakis, G., Mavromoustakis, C., Pallis, E., Markakis, E.K. (eds) Intelligent Technologies for Internet of Vehicles. Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-030-76493-7_12

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  • DOI: https://doi.org/10.1007/978-3-030-76493-7_12

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