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Internet of Vehicles: Security and Research Roadmap

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Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems

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Abstract

Evolution of ultra-fast and reliable communication infrastructures have opened up new possibilities of applications in many industries, including urban transport systems. As the number of interconnected vehicles grows, new requirements for vehicular networks emerge. The original notion of vehicular ad-hoc networks (VANET) is morphing into a new concept known as the Internet of Vehicles (IoV). In this chapter, various challenges of secure automotive system design in the context of IoV and latest industry standards are discussed. One of the focus is naturally on the Autonomous Vehicle (AV). After reviewing various communication protocols for the smooth operations of IoV the privacy and security challenges are outlined. The known vulnerabilities in an IoV are identified and classified. To obtain a robust IoV infrastructure, various techniques originating from cryptography are being deployed. The chapter is concluded with an overview of such security measures.

Cyber Security Research Centre (CYSREN), Nanyang Technological University & DESAY SV Automotive.

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Author information

Authors and Affiliations

  1. Cybersecurity and Business Analytics, Operations and Information Management Department, Aston Business School, Aston University, Birmingham, UK

    Arunmozhi Manimuthu

  2. Cyber Security Research Centre (CYSREN), Nanyang Technological University, Singapore, Singapore

    Tu Ngo

  3. School of Computer Science, Nanyang Technological University, Singapore, Singapore

    Anupam Chattopadhyay

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  1. Arunmozhi Manimuthu
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  2. Tu Ngo
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  3. Anupam Chattopadhyay
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Correspondence to Arunmozhi Manimuthu .

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Editors and Affiliations

  1. NVIDIA, Santa Clara, CA, USA

    Vipin Kumar Kukkala

  2. Colorado State University, Fort Collins, CO, USA

    Sudeep Pasricha

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Manimuthu, A., Ngo, T., Chattopadhyay, A. (2023). Internet of Vehicles: Security and Research Roadmap. In: Kukkala, V.K., Pasricha, S. (eds) Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems. Springer, Cham. https://doi.org/10.1007/978-3-031-28016-0_8

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  • DOI: https://doi.org/10.1007/978-3-031-28016-0_8

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