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

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, 97
Release date:	November 2021
First published:	2022
Editors:	John MacIntyre • Jinghua Zhao • Xiaomeng Ma
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	1154
Edition:	1st ed. 2022
ISBN-13:	978-3-03-089507-5
Categories:	Books > Computing & IT > Computer communications & networking > Network security Books > Computing & IT > Applications of computing > Databases > General Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	3-03-089507-6
Barcode:	9783030895075

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