Description

Book Synopsis

Cybersecurity in Robotic Autonomous Vehicles introduces a novel Intrusion Detection System (IDS) specifically designed for AVs, which leverages data prioritization in CAN IDs to enhance threat detection and mitigation. It offers a pioneering intrusion detection model for AVs that uses machine and deep learning algorithms.

Presenting a new method for improving vehicle security, the book demonstrates how the IDS have incorporated machine learning and deep learning frameworks to analyze CAN Bus traffic and identify the presence of any malicious activities in real time with high level of accuracy. It provides a comprehensive examination of the cybersecurity risks faced by AVs with a particular emphasis on CAN vulnerabilities and the innovative use of data prioritization within CAN IDs.

The book will interest researchers and advanced undergraduate students taking courses in cybersecurity, automotive engineering, and data science. Automotive industry and robotics profes

Cybersecurity in Robotic Autonomous Vehicles

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    A Hardback by Ahmed Alruwaili

    £999.99

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      Book details

      Publisher CRC Press
      Published 3/26/2025
      ISBN-13 9781041006404
      978-1041006404
      ISBN-10 1041006403
      Also in:
      Technology, Engineering & Agriculture Mechanical engineering

      Description

      Book Synopsis

      Cybersecurity in Robotic Autonomous Vehicles introduces a novel Intrusion Detection System (IDS) specifically designed for AVs, which leverages data prioritization in CAN IDs to enhance threat detection and mitigation. It offers a pioneering intrusion detection model for AVs that uses machine and deep learning algorithms.

      Presenting a new method for improving vehicle security, the book demonstrates how the IDS have incorporated machine learning and deep learning frameworks to analyze CAN Bus traffic and identify the presence of any malicious activities in real time with high level of accuracy. It provides a comprehensive examination of the cybersecurity risks faced by AVs with a particular emphasis on CAN vulnerabilities and the innovative use of data prioritization within CAN IDs.

      The book will interest researchers and advanced undergraduate students taking courses in cybersecurity, automotive engineering, and data science. Automotive industry and robotics profes

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