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
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| 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 |
| 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