The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy : SPIoT-2020. Volume 1 / John MacIntyre, Jinghua Zhao, Xiaomeng Ma, editors.
SPIoT (Conference) (2020 : Online); MacIntyre, J. D. (John D.), editor.; Zhao, Jinghua, editor.; Ma, Xiaomeng, editor.
2021
TK5105.8857 .S65 2020
Available Online

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Title The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy : SPIoT-2020. Volume 1 / John MacIntyre, Jinghua Zhao, Xiaomeng Ma, editors.
Meeting Name SPIoT (Conference) (2020 : Online)
ISBN 9783030627430 (electronic bk.)
3030627438 (electronic bk.)
303062742X
9783030627423
3030627454
9783030627454
DOI https://doi.org/10.1007/978-3-030-62743-0
Published Cham, Switzerland : Springer, [2021]
Language English
Description 1 online resource
Other Standard Identifiers 10.1007/978-3-030-62743-0 doi
Call Number TK5105.8857 .S65 2020
Dewey Decimal Classification 004.678
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.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Digital File Characteristics text file
PDF
Source of Description Online resource; title from digital title page (viewed on January 20, 2021).
Added Author MacIntyre, J. D. (John D.), editor.
Zhao, Jinghua, editor.
Ma, Xiaomeng, editor.
Series Advances in intelligent systems and computing ; 1282.
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
Intro
Foreword
Organization
General Chairs
Program Chairs
Publication Chairs
Publicity Chairs
Local Organizing Chairs
Program Committee Members
2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020)
Conference Program
Greeting Message

Conference Program at a Glance Friday, Nov. 6, 2020, Tencent Meeting9:50-10:00Opening ceremonyJinghua Zhao10:00-10:40Keynote 1: John Macintyre10:40-11:20Keynote 2: Junchi Yan11:20-11:40Best Paper AwardsXiaomeng Ma14:00-18:00Session 1Shunxiang ZhangSession 2Xianchao WangSession 3Xiao WeiSession 4Shaorong SunSession 5Ranran LiuSession 6Jun YeSession 7Qingyuan ZhouShort papers poster
SPIoT 2020 Keynotes
The Next Industrial Revolution: Industry 4.0 and the Role of Artificial Intelligence
Unsupervised Learning of Optical Flow with Patch Consistency and Occlusion Estimation

Oral Presentation Instruction
Short Paper Presentation Instruction
Registration
Contents
Novel Machine Learning Methods for IoT Security
The Innovation of UI Design Courses in Higher Vocational Colleges Based on the Internet Perspective
Abstract
1 Introduction
2 UI Design Development History
2.1 User Interface Design
2.2 Functional User Interface Design
2.3 Humanistic User Interface Design
2.4 Humanistic User Interface Design
3 The Current State of UI Design Courses
3.1 The Teaching Status of UI Design Courses in Vocational Colleges

3.2 Deficiencies in UI Design Course Teaching
4 Innovative Suggestions for UI Design Courses from the Perspective of the Internet
4.1 Offer Relevant Courses in Combination with Employment Orientation
4.2 The Improvement of Teachers' Professional Skills
4.3 Using the Internet to Adopt Mathematical Design
5 Conclusion
Acknowledgments
References
Predicting the Getting-on and Getting-off Points Based on the Traffic Big Data
Abstract
1 Introduction
2 Data Cleaning
2.1 First Round of Data Cleaning
2.2 Second Round of Data Cleaning
3 Algorithm Selection

3.1 K-Means
3.2 DBscan Algorithm
3.3 Algorithm Selection
4 Model Establishment Based on Dbscan Algorithm
4.1 Modeling
4.2 Clustering
5 Visualization Section
5.1 Implementation Process
5.2 Track Correction
6 Implementation Process and Experimental Results
References
The Prediction Analysis of Passengers Boarding and Alighting Points Based on the Big Data of Urban Traffic
Abstract
1 The Introduction
2 Data Cleaning
2.1 Data Cleaning in Non-Yan'an Area
2.2 Cleaning up Wrong Data and Missing Key Data Items

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