The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy
Author: John Macintyre
Publisher: Springer Nature
Total Pages: 1169
Release: 2021-10-27
Genre: Computers
ISBN: 3030895084
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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.

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy
Author: John Macintyre
Publisher: Springer Nature
Total Pages: 999
Release: 2021-11-02
Genre: Computers
ISBN: 3030895114
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Download The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy Book in PDF, Epub and Kindle

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.

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy
Author: John MacIntyre
Publisher: Springer Nature
Total Pages: 907
Release: 2020-11-03
Genre: Computers
ISBN: 3030627438
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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.

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy
Author: John MacIntyre
Publisher: Springer Nature
Total Pages: 887
Release: 2020-11-04
Genre: Computers
ISBN: 3030627462
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Download The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy Book in PDF, Epub and Kindle

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.

Big Data Analytics

Big Data Analytics
Author: Satish Narayana Srirama
Publisher: Springer Nature
Total Pages: 360
Release: 2022-01-01
Genre: Computers
ISBN: 3030936201
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This book constitutes the proceedings of the 8th International Conference on Big Data Analytics, BDA 2021, which took place during December 2021. Due to COVID-19 pandemic the conference was held virtually. The 16 full and 3 short papers included in this volume were carefully reviewed and selected from 41 submissions. The contributions were organized in topical sections named as follows: medical and health applications; machine/deep learning; IoTs, sensors, and networks; fundamentation; pattern mining and data analytics.

2021 International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications

2021 International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications
Author: George A. Tsihrintzis
Publisher: Springer Nature
Total Pages: 406
Release: 2022-11-29
Genre: Technology & Engineering
ISBN: 3031054911
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This book aims to attract researchers and practitioners who are working in information technology and computer science. This edited book is about basics and high-level concepts regarding blockchain technology and application, multimedia security, information processing, security of network, cloud and IoT, cryptography and information hiding, cyber-security and evidence investigations, and learning and intelligent computing. It is becoming increasingly important to develop adaptive, intelligent computing-centric, energy-aware, secure, and privacy-aware mechanisms in high-performance computing and IoT applications. The book serves as a useful guide for industry persons and also helps beginners to learn things from basic to advance in the area of better computing paradigm. Our aim is intended to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results in security-related areas. We believe that this book not only presents novel and interesting ideas but also will stimulate interesting discussions from the participants and inspire new ideas.

Future Data and Security Engineering

Future Data and Security Engineering
Author: Tran Khanh Dang
Publisher: Springer Nature
Total Pages: 428
Release: 2021-11-18
Genre: Computers
ISBN: 3030913872
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This book constitutes the proceedings of the 8th International Conference on Future Data and Security Engineering, FDSE 2021, which was supposed to be held in Ho Chi Minh City, Vietnam, in November 2021, but the conference was held virtually due to the COVID-19 pandemic. The 24 full papers presented together with 2 invited keynotes were carefully reviewed and selected from 168 submissions. The selected papers are organized into the following topical headings: Big Data Analytics and Distributed Systems; Advances in Machine Learning for Big Data Analytics; Industry 4.0 and Smart City: Data Analytics and Security; Blockchain and IoT Applications; Machine Learning and Artificial Intelligence for Security and Privacy; Emerging Data Management Systems and Applications.

Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021)

Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021)
Author: Rajiv Misra
Publisher: Springer Nature
Total Pages: 362
Release: 2021-09-29
Genre: Computers
ISBN: 3030824691
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This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for researchers and practitioners in the disciplines of computer science, electronics and telecommunication, information science, and electrical engineering. Machine learning and Big data analytics represent a key ingredients in the industrial applications for new products and services. Big data analytics applies machine learning for predictions by examining large and varied data sets—i.e., big data—to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more informed business decisions.

Proceedings of the International Conference on Big Data, IoT, and Machine Learning

Proceedings of the International Conference on Big Data, IoT, and Machine Learning
Author: Mohammad Shamsul Arefin
Publisher: Springer Nature
Total Pages: 784
Release: 2021-12-03
Genre: Technology & Engineering
ISBN: 9811666369
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This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox’s Bazar, Bangladesh, during 23–25 September 2021. The book covers research papers in the field of big data, IoT and machine learning. The book will be helpful for active researchers and practitioners in the field.

Future Connected Technologies

Future Connected Technologies
Author: Maanak Gupta
Publisher: CRC Press
Total Pages: 249
Release: 2023-07-17
Genre: Computers
ISBN: 1000918955
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The main aim of the book is to familiarize readers with the concepts of convergence of different connected and smart domains that are assisted by Cloud Computing, core technologies behind Cloud Computing, driving factors towards Cloud Computing, and security challenges and proposed solutions in Cloud Computing. The book covers not only the cloud, but also other pertinent topics such as Machine Learning, Deep Learning, IoT and Fog/Edge Computing. The last section of the book mainly focuses on the security aspects of connected technologies. The highpoints of the book is that it reviews the relation and combination of the mentioned topics, which together creates a better understanding about almost every aspect of Cloud Computing & related technologies.