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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy: SPIoT-2020, Volume 1 (Advances in Intelligent Systems and Computing, 1282)

Edit� par Springer, 2020

ISBN 10 : 303062742X ISBN 13 : 9783030627423

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Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis

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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

Macintyre, John|Zhao, Jinghua|Ma, Xiaomeng

Edit� par Springer International Publishing, 2020

ISBN 10 : 303062742X ISBN 13 : 9783030627423

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Includes researches in the field of Machine Learning and Big Data Analytics for IoT Security and PrivacyPresents the proceedings of the 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security . N� de r�f. du vendeur 412463905

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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

John Macintyre

Edit� par Springer International Publishing Nov 2020, 2020

ISBN 10 : 303062742X ISBN 13 : 9783030627423

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field. 916 pp. Englisch. N� de r�f. du vendeur 9783030627423

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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy: SPIoT-2020, Volume 1 (Advances in Intelligent Systems and Computing, 1282)

Edit� par Springer, 2020

ISBN 10 : 303062742X ISBN 13 : 9783030627423

Neuf Couverture souple

Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni

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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy : SPIoT-2020, Volume 1

John Macintyre

Edit� par Springer International Publishing, Springer International Publishing, 2020

ISBN 10 : 303062742X ISBN 13 : 9783030627423

Neuf Taschenbuch

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field. N� de r�f. du vendeur 9783030627423

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