ABSTRACT
This new book brings together the most recent trends related to AI, machine learning, and network security. The chapters cover diverse topics on machine learning algorithms and security analytics, AI and machine learning, and ntework security applications. The volume presents a survey of speculative parallelism techniques, performance reviews, and efficient power consumption. The book also covers the concepts of IoT, security early detection for COVID-19, multimetric geoprahpical routing in VANETs, V2X communication in VANET, and optimization of congestion control scheme for VANETs.
This book is a comprehensive take on recent applications and advancement in the field of computer science and will be of value to scientists, researchers, faculty, and students involved in research in the area of AI, machine learning, and network security.
TABLE OF CONTENTS
part I|109 pages
Machine Learning Algorithms in Security Analytics
chapter Chapter 1|14 pages
Speculative Parallelism on Multicore Chip Architecture Strengthen Green Computing Concept: A Survey
chapter Chapter 2|12 pages
Measuring Perceived Quality of Software Ecosystem Based on Transactions in Customer Management Tools
chapter Chapter 4|16 pages
Uav-Enabled Disaster Management: Applications, Open Issues, and Challenges
part II|169 pages
AI and Machine Learning
chapter Chapter 11|11 pages
Apriori-Based Algorithms with A Decentralized Approach for Mining Frequent Itemsets: A Review
chapter Chapter 16|15 pages
Performance Evaluation of a Multiband Embroidered Fractal Antenna on the Human Body
chapter Chapter 18|10 pages
Smart Card-Based Privacy Preserving Light-Weight Authentication Protocol for E-Payment Systems
part III|93 pages
Network Security Applications
