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Book cover Learning-based VANET Communication and Security Techniques

Part of the book series: Wireless Networks ((WN))

Abstract

Vehicular Ad Hoc Networks (VANETs) provides the efficient dissemination of information among the vehicles and roadside infrastructure. However, due to the high mobility of onboard units (OBUs) and the large-scale network topology, VANETs are vulnerable to attacks. In this chapter, we first review the fundamentals of VANETs in Section 1.1. Next, the type of attacks in VANETs is presented in Section 1.2, including the scope of the attack, and the impact to VANETs. We review the VANETs security solutions based on machine learning techniques including supervised learning, unsupervised learning and reinforcement learning in Section 1.3. Finally, we conclude in Section 1.4.

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Author information

Authors and Affiliations

  1. Department of Communication Engineering, Xiamen University, Xiamen, Fujian, China

    Liang Xiao

  2. Department of Electrical & Computer Engineering, University of Waterloo, Waterloo, ON, Canada

    Weihua Zhuang

  3. Department of Electronic Engineering, Tsinghua University, Beijing, China

    Sheng Zhou

  4. Department of Automation, Shanghai Jiao Tong University, Shanghai, China

    Cailian Chen

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  1. Liang Xiao
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  2. Weihua Zhuang
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  3. Sheng Zhou
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  4. Cailian Chen
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Xiao, L., Zhuang, W., Zhou, S., Chen, C. (2019). Introduction. In: Learning-based VANET Communication and Security Techniques. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-01731-6_1

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  • DOI: https://doi.org/10.1007/978-3-030-01731-6_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01730-9

  • Online ISBN: 978-3-030-01731-6

  • eBook Packages: EngineeringEngineering (R0)

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