The 2021 International Conference on Machine Learning and Big Data Analytics for Iot Security and Privacy: Spiot-2021 Volume 2

ISBN-13: 9783030895105 / Angielski / Miękka / 2021 / 1008 str.

John Macintyre; Jinghua Zhao; Xiaomeng Ma

Spis treści

Analysis of Sentiment Tendency of Tourists' Comments Based on Text Mining.- Analysis of Smart City Construction Based on 5G Data Technology.- Prediction of Stock Price Based on Artificial Intelligence Algorithm.- Variation Translation Strategy System of Intangible Cultural Heritage Based on Data Mining.- A Computer-aided Comparative Study on Grammatical Cohesion in Abstracts of Sci-tech Journal Papers by Chinese and American Scholars.- Computer Graphics and Image Software in Advertising Design.- Design and Research of Production Information Management System for Project Based Mechanical Manufacturing Enterprises.- Impact of Computer Network Technology on Regional Economic Development.- Chaos Algorithm of Electrical Control System Based on Neural Network Technology.- Pulse Signal Acquisition System Based on Match Pursuit Algorithm.- Data Analysis of Power System Engineering Construction Based on PPSO Algorithm.- Reactive Optimization of Power System Based on K-means Algorithm.- Design and Structure Analysis of Manipulator based on Acceleration Sensor.- Discussion on Decision Tree Algorithm in University Teaching Management System.

 

Blurb

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.