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The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and PrivacySPIoT-2021.Volume 1 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacyedited by John Macintyre, Jinghua Zhao, Xiaomeng Ma.
其他題名:	SPIoT-2021.
其他題名:	SPIoT-2021
其他作者:	Macintyre, John.
團體作者:
出版者:	Cham :Springer International Publishing :2022.
面頁冊數:	xxi, 1154 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Internet of thingsCongresses.Security measures
電子資源:	https://doi.org/10.1007/978-3-030-89508-2
ISBN:	9783030895082$q(electronic bk.)

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and PrivacySPIoT-2021.Volume 1 /
The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and PrivacySPIoT-2021.Volume 1 /[electronic resource] :SPIoT-2021edited by John Macintyre, Jinghua Zhao, Xiaomeng Ma. - Cham :Springer International Publishing :2022. - xxi, 1154 p. :ill. (some col.), digital ;24 cm. - Lecture notes on data engineering and communications technologies,v. 972367-4520 ;. - Lecture notes on data engineering and communications technologies ;v.2..

Application of Artificial Intelligence in Arrangement Creation -- Automatic Segmentation for Retinal Vessel Using Concatenate UNet++ -- Experimental Analysis of Mandarin Tone Pronunciation of Tibetan College Students for Artificial Intelligence Speech Recognition -- Exploration of Paths for Artificial Intelligence Technology to Promote Economic Development -- Influence of RPA Financial Robot on Financial Accounting and its Countermeasures -- Application of Artificial Intelligence Technology in English Online Learning Platform -- Spectral Identification Model of NIR Origin Based on Deep Extreme Learning Machine -- Frontier Application and Development Trend of Artificial Intelligence in New Media in the AI Era -- Analysis on the Application of Machine Learning Stock Selection Algorithm in the Financial Field -- Default Risk Prediction Based on Machine Learning under Big Data Analysis Technology -- Application of Intelligent Detection Technology and Machine Learning Algorithm in Music Intelligent System -- Application of 3D Computer Aided System in Dance Creation and Learning -- Data Selection and Machine Learning Algorithm Application under the Background of Big Data.

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.

ISBN: 9783030895082$q(electronic bk.)

Standard No.: 10.1007/978-3-030-89508-2doiSubjects--Topical Terms:

773751
Internet of things
--Security measures--Congresses.

LC Class. No.: TK5105.8857

Dewey Class. No.: 004.678

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520 $a 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.
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