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The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy - SPIoT-2021 Volume 2 (Paperback, 1st ed. 2022) Loot Price: R5,378
Discovery Miles 53 780
The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy - SPIoT-2021 Volume 2...

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy - SPIoT-2021 Volume 2 (Paperback, 1st ed. 2022)

John MacIntyre, Jinghua Zhao, Xiaomeng Ma

Series: Lecture Notes on Data Engineering and Communications Technologies, 98

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Loot Price R5,378 Discovery Miles 53 780 | Repayment Terms: R504 pm x 12*

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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.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Series: Lecture Notes on Data Engineering and Communications Technologies, 98
Release date: November 2021
First published: 2022
Editors: John MacIntyre • Jinghua Zhao • Xiaomeng Ma
Dimensions: 235 x 155mm (L x W)
Format: Paperback
Pages: 986
Edition: 1st ed. 2022
ISBN-13: 978-3-03-089510-5
Categories: Books > Professional & Technical > Energy technology & engineering > Electrical engineering > General
Books > Computing & IT > Applications of computing > Databases > General
Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN: 3-03-089510-6
Barcode: 9783030895105

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