Cybersecurity in Robotic Autonomous Vehicles: Machine Learning Applications to Detect Cyber Attacks (1)

Synopsis

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.

Copyright:

2025

Book Details

Book Quality:

Publisher Quality

Book Size:

106 Pages

ISBN-13:

9781040358702

Related ISBNs:

9781040358696, 9781041006404, 9781003610908

Publisher:

CRC Press

Date of Addition:

03/21/25

Copyrighted By:

Ahmed Alruwaili, Sardar M.N. Islam, and Iqbal Gondal. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use.

Adult content:

No

Language:

English

Has Image Descriptions:

No

Categories:

Nonfiction, Computers and Internet, Technology

Submitted By:

Bookshare Staff

Usage Restrictions:

This is a copyrighted book.