Advanced Computer Science Applications : Recent Trends in AI, Machine Learning, and Network Security

Sign Language ASP automatic speculative parallelization AUT antenna under test BoG Board of Governors BSL British Sign Language BSs base stations CA certification authority CC correlation coefficient CH cluster heads CNN convolutional neural network CRL certificate revocation list CRM customer relationship management CVS cooperative vehicle safety DAG directed acyclic graph DAO DODAG advertisement object DDoS distributed denial of service DEC deterministic energy-efficient clustering protocol DHCP Dynamic Host Configuration Protocol DIO DODAG information object DIS DODAG information solicitation DM data mining DOM document entity model DoS denial of service DPA Distributed Parallel Apriori DSRC dedicated short-range communication DST Department of Science and Technology DTCWT dual-tree complex wavelet transforms ECC elliptic curve cryptosystem ERP enterprise resource planning FANETs flying ad hoc networks FBR final beacon rate xxiv Preface This will only broaden the threat environment and give criminals more ways and opportunities to commit crimes. This part covers the concepts of IoT, security early detections for COVID-19, multimetric geographical routing in VANETs, V2X communication in VANET, and optimization of congestion control scheme for VANETs. We hope that the information conveyed in these chapters will give the reader have a firm grasp of the methods in the field of artificial intelligence, machine learning, and security. Cover Half Title Title Page Copyright Page Series Page About the Editors Table of Contents Contributors Abbreviations Preface Part I: Machine Learning Algorithms in Security Analytics 1. Speculative Parallelism on Multicore Chip Architecture Strengthen Green Computing Concept: A Survey 2. Measuring Perceived Quality of Software Ecosystem Based on Transactions in Customer Management Tools 3. Moving Object Detection in Video, Captured by Static Camera: A Survey 4. UAV-Enabled Disaster Management: Applications, Open Issues, and Challenges 5. Cross-Site Scripting Attack Prevention (on Application Layer) 6. TBM-Based Charger Deployment Technique in the Internet of Things 7. Data Mining for Internet of the Things: A Survey Part II: AI and Machine Learning 8. Classification of Web User Interest Level Using Web Usage Mining 9. Design and Development of AI-Assisted Smart Ventilators 10. Descriptive Review on a Nepali Sign Language Recognition System 11. Apriori-Based Algorithms with a Decentralized Approach for Mining Frequent Item Sets: A Review 12. Impact of Artificial Intelligence and Internet of Things in Modern Times and Hereafter: An Investigative Analysis 13. Intelligent Post-Lockdown Management System for Public Transportation 14. Smart Walking Stick (for the Blind) 15. Dynamic Nepali Sign Language Recognition 16. Performance Evaluation of a Multiband Embroidered Fractal Antenna on The Human Body 17. Learning Deep Representation Using a Fully Convolutional Autoencoder for Automated Floor Plan Image Retrieval 18. Smart Card-Based Privacy Preserving Light-Weight Authentication Protocol for E-Payment Systems 19. DEC-GA: Genetic Algorithm-Based Deterministic Energy-Efficient Clustering Protocol for IOT Transactions in Customer Management Tools 20. Hashtag Recommendation System to Track Streaming News and Capture Dynamic Evolution to Ensure High Coverage (CADENCE) Part III: Network Security Applications 21. Mitigation of RPL Stateless Address Auto-Configuration IPv6 Spoofing Attack in IoT 22. Secure and Early Detection Framework for COVID-19: Standardization of Clinical Process 23. Probabilistic Image Encryption-Based Secure Surveillance Framework for an IoT Environment 24. An Enhanced Approach for Multimetric Geographical Routing in VANETs Using a Fuzzy Interface System 25. Energy-Efficient Privacy Preserving Vehicle Registration Protocol for V2X Communication in VANET 26. Evaluation and Optimization of a Congestion Control Scheme for VANETs 27. Dispute Between Countries, a Corresponding Attack on Cyberspace: The New National Security Challenge Index "Artificial intelligence (AI) and machine learning (ML) are two areas of computer science that have seen drastic advancement in recent years. Keeping track of this rapid development, this book, Advanced Computer Science Applications: Recent Trends in AI, Machine Learning, and Network Security, brings together the most recent trends related to AI, ML and Network Security. The book consists of three parts with each part focusing on a specific aspect of AI, machine learning, and network security. The chapters cover such diverse topics including machine learning algorithms and security analytics, AI and machine learning, and network security applications. The book presents a variety of design algorithms including convolutional neural networks (CNN), random forest algorithm, k-nearest neighbor (KNN), Apriori algorithm, MapReduce algorithm, and the Genetic Algorithm used in IoT applications. The volume presents a survey of speculative parallelism techniques, performance reviews, and efficient power consumption. It discusses measuring perceived quality of software ecosystems based on transactions in customer management tools and offers a study of the background modelling and background subtraction along with various other literature studies that justify the role of moving object detection in computer vision. The book also covers the concepts of IoT, security early detections for COVID-19, multimetric geographical 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. Scientists, researchers, faculty, and students involved in research in the area of AI, machine learning, and network security will find valuable information in this volume."-- Provided by publisher 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. Discusses design algorithms that allow computers to employ machine learning to display behavior learned from past experiences for solutions to security issues in data management. Algorithms discussed include convolutional neural network, random forest algorithm, k-nearest neighbor algorithm, Apriori algorithm, MapReduce algorithm, etc.