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Cybersecurity in Robotic Autonomous Vehicles

- Machine Learning Applications to Detect Cyber Attacks
Af: Sardar M. N. Islam, Iqbal Gondal, Ahmed Alruwaili Engelsk Hardback

Cybersecurity in Robotic Autonomous Vehicles

- Machine Learning Applications to Detect Cyber Attacks
Af: Sardar M. N. Islam, Iqbal Gondal, Ahmed Alruwaili Engelsk Hardback
Tjek vores konkurrenters priser

Cybersecurity in Robotic Autonomous Vehicles introduces a novel intrusion detection system (IDS) specifically designed for AVs, which leverages data prioritisation 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 has incorporated machine learning and deep learning frameworks to analyse 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 prioritisation 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 professionals focusing on Internet of Vehicles and cybersecurity will also benefit from the contents.

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Fragt: 39 kr
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Cybersecurity in Robotic Autonomous Vehicles introduces a novel intrusion detection system (IDS) specifically designed for AVs, which leverages data prioritisation 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 has incorporated machine learning and deep learning frameworks to analyse 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 prioritisation 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 professionals focusing on Internet of Vehicles and cybersecurity will also benefit from the contents.

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Produktdetaljer
Sprog: Engelsk
Sider: 90
ISBN-13: 9781041006404
Indbinding: Hardback
Udgave:
ISBN-10: 1041006403
Kategori: Robotteknik
Udg. Dato: 20 mar 2025
Længde: 13mm
Bredde: 224mm
Højde: 144mm
Forlag: Taylor & Francis Ltd
Oplagsdato: 20 mar 2025
Forfatter(e): Sardar M. N. Islam, Iqbal Gondal, Ahmed Alruwaili
Forfatter(e) Sardar M. N. Islam, Iqbal Gondal, Ahmed Alruwaili

Kategori Robotteknik

ISBN-13 9781041006404

Sprog Engelsk

Indbinding Hardback

Sider 90

Udgave

Længde 13mm

Bredde 224mm

Højde 144mm

Udg. Dato 20 mar 2025

Oplagsdato 20 mar 2025

Forlag Taylor & Francis Ltd