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Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032206454 ISBN 13: 9781032206455
Language: English
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Paperback. Condition: new. Paperback. The integration of fog computing with the resource-limited Internet of Things (IoT) network formulates the concept of the fog-enabled IoT system. Due to a large number of IoT devices, the IoT is a main source of Big Data. A large volume of sensing data is generated by IoT systems such as smart cities and smart-grid applications. A fundamental research issue is how to provide a fast and efficient data analytics solution for fog-enabled IoT systems. Big Data Analytics in Fog-Enabled IoT Networks: Towards a Privacy and Security Perspective focuses on Big Data analytics in a fog-enabled-IoT system and provides a comprehensive collection of chapters that touch on different issues related to healthcare systems, cyber-threat detection, malware detection, and the security and privacy of IoT Big Data and IoT networks.This book also emphasizes and facilitates a greater understanding of various security and privacy approaches using advanced artificial intelligence and Big Data technologies such as machine and deep learning, federated learning, blockchain, and edge computing, as well as the countermeasures to overcome the vulnerabilities of the fog-enabled IoT system. This book emphasizes and facilitate a greater understanding of various security and privacy approaches using the advance AI and Big data technologies like machine/deep learning, federated learning, blockchain, edge computing and the countermeasures to overcome the vulnerabilities of the Fog-enabled IoT system. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032206454 ISBN 13: 9781032206455
Language: English
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Add to basketPaperback. Condition: Brand New. 232 pages. 9.18x6.12x9.21 inches. In Stock.
Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032206454 ISBN 13: 9781032206455
Language: English
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Add to basketPaperback. Condition: new. Paperback. The integration of fog computing with the resource-limited Internet of Things (IoT) network formulates the concept of the fog-enabled IoT system. Due to a large number of IoT devices, the IoT is a main source of Big Data. A large volume of sensing data is generated by IoT systems such as smart cities and smart-grid applications. A fundamental research issue is how to provide a fast and efficient data analytics solution for fog-enabled IoT systems. Big Data Analytics in Fog-Enabled IoT Networks: Towards a Privacy and Security Perspective focuses on Big Data analytics in a fog-enabled-IoT system and provides a comprehensive collection of chapters that touch on different issues related to healthcare systems, cyber-threat detection, malware detection, and the security and privacy of IoT Big Data and IoT networks.This book also emphasizes and facilitates a greater understanding of various security and privacy approaches using advanced artificial intelligence and Big Data technologies such as machine and deep learning, federated learning, blockchain, and edge computing, as well as the countermeasures to overcome the vulnerabilities of the fog-enabled IoT system. This book emphasizes and facilitate a greater understanding of various security and privacy approaches using the advance AI and Big data technologies like machine/deep learning, federated learning, blockchain, edge computing and the countermeasures to overcome the vulnerabilities of the Fog-enabled IoT system. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Add to basketTaschenbuch. Condition: Neu. Neuware - This book emphasizes and facilitate a greater understanding of various security and privacy approaches using the advance AI and Big data technologies like machine/deep learning, federated learning, blockchain, edge computing and the countermeasures to overcome the vulnerabilities of the Fog-enabled IoT system.
Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032206454 ISBN 13: 9781032206455
Language: English
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Add to basketPaperback. Condition: new. Paperback. The integration of fog computing with the resource-limited Internet of Things (IoT) network formulates the concept of the fog-enabled IoT system. Due to a large number of IoT devices, the IoT is a main source of Big Data. A large volume of sensing data is generated by IoT systems such as smart cities and smart-grid applications. A fundamental research issue is how to provide a fast and efficient data analytics solution for fog-enabled IoT systems. Big Data Analytics in Fog-Enabled IoT Networks: Towards a Privacy and Security Perspective focuses on Big Data analytics in a fog-enabled-IoT system and provides a comprehensive collection of chapters that touch on different issues related to healthcare systems, cyber-threat detection, malware detection, and the security and privacy of IoT Big Data and IoT networks.This book also emphasizes and facilitates a greater understanding of various security and privacy approaches using advanced artificial intelligence and Big Data technologies such as machine and deep learning, federated learning, blockchain, and edge computing, as well as the countermeasures to overcome the vulnerabilities of the fog-enabled IoT system. This book emphasizes and facilitate a greater understanding of various security and privacy approaches using the advance AI and Big data technologies like machine/deep learning, federated learning, blockchain, edge computing and the countermeasures to overcome the vulnerabilities of the Fog-enabled IoT system. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Published by Taylor & Francis Ltd, 2023
ISBN 10: 1032206446 ISBN 13: 9781032206448
Language: English
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Published by Taylor & Francis Ltd, London, 2023
ISBN 10: 1032206446 ISBN 13: 9781032206448
Language: English
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Add to basketHardcover. Condition: new. Hardcover. The integration of fog computing with the resource-limited Internet of Things (IoT) network formulates the concept of the fog-enabled IoT system. Due to a large number of IoT devices, the IoT is a main source of Big Data. A large volume of sensing data is generated by IoT systems such as smart cities and smart-grid applications. A fundamental research issue is how to provide a fast and efficient data analytics solution for fog-enabled IoT systems. Big Data Analytics in Fog-Enabled IoT Networks: Towards a Privacy and Security Perspective focuses on Big Data analytics in a fog-enabled-IoT system and provides a comprehensive collection of chapters that touch on different issues related to healthcare systems, cyber-threat detection, malware detection, and the security and privacy of IoT Big Data and IoT networks.This book also emphasizes and facilitates a greater understanding of various security and privacy approaches using advanced artificial intelligence and Big Data technologies such as machine and deep learning, federated learning, blockchain, and edge computing, as well as the countermeasures to overcome the vulnerabilities of the fog-enabled IoT system. This book emphasizes and facilitate a greater understanding of various security and privacy approaches using the advance AI and Big data technologies like machine/deep learning, federated learning, blockchain, edge computing and the countermeasures to overcome the vulnerabilities of the Fog-enabled IoT system. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Add to basketHardcover. Condition: Brand New. 264 pages. 9.19x6.13x0.83 inches. In Stock.
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Add to basketPaperback. Condition: Brand New. 232 pages. 9.18x6.12x9.21 inches. In Stock. This item is printed on demand.
Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032206454 ISBN 13: 9781032206455
Language: English
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Add to basketHRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.