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Security Issues and Solutions for Connected and Autonomous Vehicles in a Sustainable City: A Survey

Author

Listed:
  • Zhendong Wang

    (Department of ECE, The University of Texas at Dallas, Richardson, TX 75080, USA)

  • Haoran Wei

    (Department of ECE, The University of Texas at Dallas, Richardson, TX 75080, USA)

  • Jianda Wang

    (Department of ECE, The University of Texas at Dallas, Richardson, TX 75080, USA)

  • Xiaoming Zeng

    (Department of ECE, The University of Texas at Dallas, Richardson, TX 75080, USA)

  • Yuchao Chang

    (Department of Electronic Engineering, School of Electronic Information and Electrical Engineering, Minhang Campus, Shanghai Jiaotong University, Shanghai 200233, China)

Abstract

Connected and Autonomous Vehicles (CAVs) combine technologies of autonomous vehicles (AVs) and connected vehicles (CVs) to develop quicker, more reliable, and safer traffic. Artificial Intelligence (AI)-based CAV solutions play significant roles in sustainable cities. The convergence imposes stringent security requirements for CAV safety and reliability. In practice, vehicles are developed with increased automation and connectivity. Increased automation increases the reliance on the sensor-based technologies and decreases the reliance on the driver; increased connectivity increases the exposures of vehicles’ vulnerability and increases the risk for an adversary to implement a cyber-attack. Much work has been dedicated to identifying the security vulnerabilities and recommending mitigation techniques associated with different sensors, controllers, and connection mechanisms, respectively. However, there is an absence of comprehensive and in-depth studies to identify how the cyber-attacks exploit the vehicles’ vulnerabilities to negatively impact the performance and operations of CAVs. In this survey, we set out to thoroughly review the security issues introduced by AV and CV technologies, analyze how the cyber-attacks impact the performance of CAVs, and summarize the solutions correspondingly. The impact of cyber-attacks on the performance of CAVs is elaborated from both viewpoints of intra-vehicle systems and inter-vehicle systems. We pointed out that securing the perception and operations of CAVs would be the top requirement to enable CAVs to be applied safely and reliably in practice. Additionally, we suggested to utilize cloud and new AI methods to defend against smart cyber-attacks on CAVs.

Suggested Citation

  • Zhendong Wang & Haoran Wei & Jianda Wang & Xiaoming Zeng & Yuchao Chang, 2022. "Security Issues and Solutions for Connected and Autonomous Vehicles in a Sustainable City: A Survey," Sustainability, MDPI, vol. 14(19), pages 1-29, September.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12409-:d:929308
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    References listed on IDEAS

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    1. Volodymyr Mnih & Koray Kavukcuoglu & David Silver & Andrei A. Rusu & Joel Veness & Marc G. Bellemare & Alex Graves & Martin Riedmiller & Andreas K. Fidjeland & Georg Ostrovski & Stig Petersen & Charle, 2015. "Human-level control through deep reinforcement learning," Nature, Nature, vol. 518(7540), pages 529-533, February.
    2. Hoppe, Tobias & Kiltz, Stefan & Dittmann, Jana, 2011. "Security threats to automotive CAN networks—Practical examples and selected short-term countermeasures," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 11-25.
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    Cited by:

    1. Xingyu Li & Ruifeng Li & Yanchen Liu, 2024. "HP-LSTM: Hawkes Process–LSTM-Based Detection of DDoS Attack for In-Vehicle Network," Future Internet, MDPI, vol. 16(6), pages 1-21, May.
    2. Haoran Wei & Zhendong Wang & Yuchao Chang & Zhenghua Huang, 2022. "Introducing the Special Issue on Artificial Intelligence Applications for Sustainable Urban Living," Sustainability, MDPI, vol. 14(20), pages 1-4, October.

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