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Cybersecurity in Robotic Autonomous Vehicles : Machine Learning Applications to Detect Cyber Attacks /

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개인저자Alruwaili, Ahmed, author.
Islam, Sardar M. N., 1950-, author.
Gondal, Iqba?l, author.
서명/저자사항Cybersecurity in Robotic Autonomous Vehicles :Machine Learning Applications to Detect Cyber Attacks /Ahmed Alruwaili, Sardar M. N. Islam, Iqbal Gondal.
판사항First edition.
발행사항Boca Raton : CRC Press, Taylor & Francis Group, 2025.
형태사항1 online resource (106 pages) : illustrations.
소장본 주기OCLC control number change
ISBN9781003610908
1003610900
9781040358696
1040358691
9781040358702
1040358705

기타표준부호10.1201/9781003610908doi
내용주기1. Introduction. 2. Theoretical Lens. 3. Exploring CAN Bus Security: Insights and Analysis. 4. Research Design. 5. Results and Discussion. 6. Conclusions and Future Research.
요약Cybersecurity 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.
일반주제명Computer security.
Automated vehicles.
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