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010 a| 2024061864;

020 a| 9781041006404q| hbk;

020 a| 9781003610915q| pbk;

020 z| 9781003610908q| ebk;

035 a| (WaSeSS)ssj0003362329;

042 a| pcc;

049 a| EREEa| NEHH;

050 00 a| TL152.8b| .A46 2025;

082 00 a| 005.82| 23/eng/20250730;

100 1 a| Alruwaili, Ahmed0| http://id.loc.gov/authorities/names/n20250267461| http://id.loc.gov/rwo/agents/n2025026746.?| UNAUTHORIZED;

245 10 a| Cybersecurity in robotic autonomous vehiclesh| [electronic resource] :b| machine learning applications to detect cyber attacks /c| Ahmed Alruwaili, Sardar M.N. Islam, and Iqbal Gondal.;

250 a| First edition.;

260 a| Boca Raton, FL :b| CRC Press,c| 2025.;

263 a| 2505;

300 a| pages cm;

334 a| single unitb| mono0| http://id.loc.gov/vocabulary/issuance/mono;

353 a| bibliographyb| bibliography0| http://id.loc.gov/vocabulary/msupplcont/bibliography;

353 a| indexb| index0| http://id.loc.gov/vocabulary/msupplcont/index;

504 a| Includes bibliographical references and index.;

505 2 a| Theoretical lens. Multi-agent systems -- An overview of Internet of Vehicles (IoV) -- Robotics -- Autonomous Vehicles (AVs) -- Exploring CAN bus security : insights and analysis. Controller Area Network (CAN) -- Severity of problem -- Solutions implemented on CAN bus -- Machine learning and Intrusion Detection System.;

506 a| Available only to authorized users.;

650 0 a| Automated vehiclesx| Safety measures=| ^A1273031;

520 a| "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 professionals focusing on internet-of-vehicles and cybersecurity will also benefit from the contents"-- Provided by publisher.;

538 a| Mode of access: World Wide Web;

650 0 a| Automated vehiclesx| Security measures=| ^A1273031;

650 0 a| Computer networksx| Security measures0| http://id.loc.gov/authorities/subjects/sh94001277=| ^A388828;

650 0 a| Machine learningx| Security measures=| ^A145211;

650 0 a| Controller Area Network (Computer network)x| Security measures?| UNAUTHORIZED;

650 0 a| Computer security0| http://id.loc.gov/authorities/subjects/sh90001862=| ^A257308;

650 0 a| Hacking0| http://id.loc.gov/authorities/subjects/sh2013002597=| ^A1280113;

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758 4| http://id.loc.gov/ontologies/bibframe/instanceOf1| http://id.loc.gov/resources/works/24255420;

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Cybersecurity in robotic autonomous vehicles machine learning applications to detect cyber attacks / Ahmed Alruwaili, Sardar M.N. Islam, and Iqbal Gondal.

Author/creator	Alruwaili, Ahmed
Other author	Islam, Sardar M. N., 1950
Other author	Gondal, Iqbal (Electrical engineer
Format	Electronic
Edition	First edition.
Publication Info	Boca Raton, FL : CRC Press, 2025.
Description	pages cm
Supplemental Content	Full text available from eBooks on EBSCOhost
Subjects	Automated vehicles--Safety measures. Automated vehicles--Security measures. Computer networks--Security measures. Machine learning--Security measures. Controller Area Network (Computer network)--Security measures. Computer security Hacking

Partial contents	Theoretical lens. Multi-agent systems -- An overview of Internet of Vehicles (IoV) -- Robotics -- Autonomous Vehicles (AVs) -- Exploring CAN bus security : insights and analysis. Controller Area Network (CAN) -- Severity of problem -- Solutions implemented on CAN bus -- Machine learning and Intrusion Detection System.
Abstract	"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 professionals focusing on internet-of-vehicles and cybersecurity will also benefit from the contents"-- Provided by publisher.
Bibliography note	Includes bibliographical references and index.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Genre/form	Electronic books.
LCCN	2024061864
ISBN	9781041006404 hbk
ISBN	9781003610915 pbk
ISBN	ebk

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Cybersecurity in robotic autonomous vehicles machine learning applications to detect cyber attacks / Ahmed Alruwaili, Sardar M.N. Islam, and Iqbal Gondal.

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