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Aggiungi al carrelloHardcover. Condizione: Brand New. 104 pages. 8.50x5.43x8.50 inches. In Stock.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2025
ISBN 10: 1041006403 ISBN 13: 9781041006404
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Hardcover. Condizione: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2025
ISBN 10: 1041006403 ISBN 13: 9781041006404
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Mr. Ahmed Alruwaili is a researcher specialising in cyber security, artificial intelligence, and quantum computing. He received his Bachelor of Computer Science in computer science and information from Aljouf University, Saudi Arabia, in.
Da: preigu, Osnabrück, Germania
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Aggiungi al carrelloBuch. Condizione: Neu. Cybersecurity in Robotic Autonomous Vehicles | Machine Learning Applications to Detect Cyber Attacks | Ahmed Alruwaili (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2025 | CRC Press | EAN 9781041006404 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2025
ISBN 10: 1041006403 ISBN 13: 9781041006404
Da: AussieBookSeller, Truganina, VIC, Australia
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.