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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy [[electronic resource] ] : SPIoT-2020, Volume 1 / / edited by John MacIntyre, Jinghua Zhao, Xiaomeng Ma



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Titolo: The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy [[electronic resource] ] : SPIoT-2020, Volume 1 / / edited by John MacIntyre, Jinghua Zhao, Xiaomeng Ma Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Edizione: 1st ed. 2021.
Descrizione fisica: 1 online resource (XXXI, 884 p. 221 illus., 150 illus. in color.)
Disciplina: 620.00285
Soggetto topico: Engineering—Data processing
Cooperating objects (Computer systems)
Computational intelligence
Machine learning
Big data
Data Engineering
Cyber-Physical Systems
Computational Intelligence
Machine Learning
Big Data
Persona (resp. second.): MacIntyreJ. D (John D.)
ZhaoJinghua
MaXiaomeng
Note generali: Includes index.
Sommario/riassunto: 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.
Titolo autorizzato: The 2020 international conference on machine learning and big data analytics for IoT security and privacy  Visualizza cluster
ISBN: 3-030-62743-8
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910483068103321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Serie: Advances in Intelligent Systems and Computing, . 2194-5365 ; ; 1282