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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy : SPIoT-2020. Volume 2 / John MacIntyre, Jinghua Zhao, Xiaomeng Ma, editors.

International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (2020 : Online); MacIntyre, J. D. (John D.), editor.; Zhao, Jinghua, editor.; Ma, Xiaomeng, editor.
2021
TK5105.8857 .S65 2020eb
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Title
The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy : SPIoT-2020. Volume 2 / John MacIntyre, Jinghua Zhao, Xiaomeng Ma, editors.
Meeting Name
International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (2020 : Online)
ISBN
9783030627461 (electronic book)
3030627462 (electronic book)
DOI
https://doi.org/10.1007/978-3-030-62746-1
Published
Cham, Switzerland : Springer, [2021]
Copyright
©2021
Language
English
Description
1 online resource (xxxii, 863 pages).
Item Number
10.1007/978-3-030-62746-1 doi
Call Number
TK5105.8857 .S65 2020eb
Dewey Decimal Classification
004.67/8
Summary
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.
Note
Includes author index.
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Access limited to authorized users.
Digital File Characteristics
text file
PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed February 1, 2021).
Added Author
MacIntyre, J. D. (John D.), editor.
Zhao, Jinghua, editor.
Ma, Xiaomeng, editor.
Series
Advances in intelligent systems and computing ; 1283.
Available in Other Form
2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy : SPIoT-2020, Volume 2.
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Volume 2. Part I. Data-Driven Co-design of Communication, Computing and Control for IoT Security
Design of a Force Balance Geophone Utilizing Bandwidth Extension and Data Acquisition Interface
Application of 3ds Max Technology in Archaeology
The Application of Virtual Reality Technology in ESP Teaching
Application of Simulation Method Based on Computer Bionic Design
(Plus 29 other papers)
Part II. Authentication and Access Control for Data Usage in IoT (32 papers)
Part III. Experiments, Test-Beds and Prototyping Systems for IoT Security (29 papers)
Part IV. Short paper session (42 papers).

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