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Cyber Security and Privacy of Connected and Automated Vehicles (CAVs)-Based Federated Learning: Challenges, Opportunities, and Open Issues

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Federated Learning for IoT Applications

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

Abstract

Connected and automated vehicles (CAVs) are becoming a reality. Prototyping and testing of self-driving vehicle technology are becoming more popular around the world. The secure deployment of self-driving vehicles necessitates a wide range of technology, competencies, and procedures, all of which must be thoroughly checked and assessed, as road safety may be a risk. As a result, it’s critical to recognize and develop a thorough understanding of the cyber security and privacy concerns with CAVs and of the way these can be prioritized as well as addressed. This chapter investigates falsified information attacks against the RSU’s ongoing FL operation. We discovered a variety of attack tactics used by malicious CAVs to disrupt global system training in vehicular ad hoc networks (VANETs). In which, demonstrate the attacks effectively increased the convergence time and reduced the model’s accuracy.

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Author information

Authors and Affiliations

  1. School of Computers, IPS Academy, Indore, MP, India

    Naziya Hussain, Harsha Chouhan & Urvashi Sharma Gaur

  2. Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Delhi-NCR Campus, Delhi-Meerut Road, Modinagar, Ghaziabad, UP, India

    Preeti Rani

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  1. Naziya Hussain
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  2. Preeti Rani
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  3. Harsha Chouhan
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  4. Urvashi Sharma Gaur
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Editors and Affiliations

  1. Department of Computer Science and Engineering, G.L. Bajaj Institute of Technology and Management (GLBITM) Affiliated to AKTU, Lucknow, Uttar Pradesh, India

    Satya Prakash Yadav

  2. Department of Computer Science and Engineering, Chandigarh University, Mohali, India

    Bhoopesh Singh Bhati

  3. National Institute of Technology Hamirpur, Himachal Pradesh, India

    Dharmendra Prasad Mahato

  4. Kyungpook National University, Daegu, Korea (Republic of)

    Sachin Kumar

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Hussain, N., Rani, P., Chouhan, H., Gaur, U.S. (2022). Cyber Security and Privacy of Connected and Automated Vehicles (CAVs)-Based Federated Learning: Challenges, Opportunities, and Open Issues. In: Yadav, S.P., Bhati, B.S., Mahato, D.P., Kumar, S. (eds) Federated Learning for IoT Applications. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-85559-8_11

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