| 书目名称 | The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Pr |
| 副标题 | SPIoT-2021 Volume 1 |
| 编辑 | John Macintyre,Jinghua Zhao,Xiaomeng Ma |
| 视频video | http://file.papertrans.cn/904/903882/903882.mp4 |
| 概述 | Presents proceedings of the 2021 International Conference on Machine Learning and Big Data Analytics.Contains the state-of-the-art in IoT security and privacy.Written by experts in the field |
| 丛书名称 | Lecture Notes on Data Engineering and Communications Technologies |
| 图书封面 |  |
| 描述 | . .This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. 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. . |
| 出版日期 | Conference proceedings 2022 |
| 关键词 | Novel Machine Learning and Big Data Analytics Methods; Data Mining and Statistical Modelling for the |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-89508-2 |
| isbn_softcover | 978-3-030-89507-5 |
| isbn_ebook | 978-3-030-89508-2Series ISSN 2367-4512 Series E-ISSN 2367-4520 |
| issn_series | 2367-4512 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
|Archiver|手机版|小黑屋|
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