About the Book
Edge computing and intelligence is a new technical discipline that researches and develops theories, methods, technologies, and application systems for enabling fast and efficient processing and intelligent decision-making using the big data generated from the Internet of Things (IoT) system. The edge computing and intelligence–enabled IoT system helps in alleviating the resource limitations of IoT devices and facilitates large-scale deployment of IoT systems for different applications such as smart cities, smart grids, smart homes, smart healthcare systems, smart video surveillance, and e-healthcare.
Due to the deployment of the IoT devices in the open environment and their interaction with other IoT devices through unstable and unreliable wireless channels, as well as the placement of edge nodes near IoT systems, IoT devices offer many chances for malicious attackers to compromise them through collusion attacks, denial-of-service attacks, and many other types of attacks. Analysis of the network traffic and IoT data at the edge nodes using the latest artificial intelligence techniques will address a number of issues, such as anomaly detection in IoT data, data poisoning attacks, and other security and privacy issues related to IoT systems. In this book, we will provide an overview of the fundamental concepts of edge computing, edge intelligence using advanced machine- and deep-learning models, the architecture of edge computing–based IoT systems, and edge computing–based cyber threat intelligence solutions for IoT systems.
Table of Contents:
Chapter 1. Edge Intelligence for IoT: Architecture, Issues, and Applications
Chapter 2. Edge Intelligence based Internet of Medical Things: Architecture, Issues, and
Case Studies
Chapter 3. Edge Intelligence based Intrusion Detection and Avoidance Framework for
IoT Network
Chapter 4. Edge Intelligence based Anomaly Detection for IoT Network
Chapter 5. Edge Intelligence based Intelligent Transportation System
Chapter 6. Edge Intelligence and IoT-based Smart Agriculture System
Chapter 7. Edge Intelligence and Privacy Preservation Aware Intelligent Cyber Threats
Detection Model
Chapter 8. Edge Intelligence and Deep Learning Approaches based data analytics for
Fog-enabled IoT Network
Chapter 9. Edge Intelligence and Federated Learning based Healthcare Data Analytics
Chapter 10. Edge Intelligence and Deep Reinforcement Learning based Big Data Analytics
for IoT System
Chapter 11. Edge Intelligence and Privacy-aware Threat Intelligence for Fog-enabled IoT
Network using big data approaches.
Chapter 12. Edge Intelligence and Blockchain-based security architecture for Fog-enabled
IoT Systems
Chapter 13. Blockchain and Edge Intelligence based forensic evidence preservation in
Fog-enabled IoT Systems
Chapter 14. Edge Intelligence based Botnet detection in Fog-enabled IoT environments.
Chapter 15. Edge Intelligence based Data Analytics for Vehicular Communication
Networks
About the Author :
Govind P. Gupta is currently working as an Associate Professor in the Dept. of IT, National Institute of Technology Raipur, India. He has received his PhD in computer science and engineering from the Indian Institute of Technology, Roorkee, India. He has more than 15 years of teaching and research experience. He has made practical and theoretical contributions in big data processing and analytics, Wireless Sensor Network (WSN), Internet of Things (IoT), and cyber security domains, and his research has a significant impact on big data analytics, WSN, IoT, information, and network security against cyberattacks. He has published more than 150 research papers in reputed peer-reviewed journals and conferences of international reputes. He has received several R&D projects from prestigious funding organizations such as SERB (MATRIX), SERB(CRG) and C3iHub (IIT Kanpur). He is an active reviewer of various journals such as IEEE Internet of Things, IEEE Sensors Journal, IEEE Transactions on Green Communications, Elsevier Computer Networks, Ad-Hoc Networks, Computer Communications, and Springer Wireless Networks. His current research interests include IoT, IoT security, Edge Intelligence, network security, big IoT data analytics, blockchain-based application development for IoT, and enterprise blockchain. Dr. Gupta was recently included in the Global Alper-Doger (AD) Scientific Index 2024 list. He was also included in the 2024, 2023, 2022, and 2021 Stanford University lists of “Worlds Top 2%” scientists. He is a professional member of the IEEE and ACM.
Prof. Brij B. Gupta is working as Director of International Center for AI and Cyber Security Research and Innovations, and Distinguished Professor with the Department of Computer Science and Information Engineering (CSIE), Asia University, Taiwan. In more than 20 years of his professional experience, he published over 600 papers in journals/conferences including 35 books and 12 Patents with over 35,000 citations. He has received numerous national and international awards including Canadian Commonwealth Scholarship (2009), Faculty Research Fellowship Award (2017), MeitY, GoI, IEEE GCCE outstanding and WIE paper awards and Best Faculty Award (2018 & 2019), respectively. Prof. Gupta was selected for Clarivate Web of Science Highly Cited Researchers in Computer Science (top 0.1% researchers in the world) consecutively in 2022 and 2023. He was also selected in Stanford University’s ranking of the world’s top 2% scientists consecutively from 2019 to 2024. He is also a visiting/adjunct professor with several universities worldwide. Additionally, he is an IEEE Senior Member (2017) and was also selected as 2021 Distinguished Lecturer in IEEE CTSoc. Prof. Gupta was also a member of the Board of Governors, IEEE Consumer Technology Society (2022–2024). Prof. Gupta also leads IJSWIS, IJSSCI, and IJCAC as Editor-in-Chief. He also now serves as lead editor of a book series with CRC and IET press. He has been TPC member in more than 150 international conferences, and has been Associate/Guest Editor of various journals and publications. His research interests include information security, cyber physical systems, cloud computing, blockchain technologies, intrusion detection, AI, social media and networking.
Kumkum Garg obtained her bachelor of engineering (BE) and master of engineering (ME) from IIT Roorkee, India, and PhD from Imperial College of Science and Technology, University of London, UK. Her research interests are in computer networks, mobile computing, and AI. She has taught at the prestigious IIT Roorkee for 35 years. She has served as director at Manipal University and as the Dean, Faculty of Informatics, Photonics, and Robotics at Bhartiya Skill Development University, Jaipur, India. Currently, she is Honorary Professor at The North Cap University, Gurugram, India. She was awarded the Apple Distinguished Educator (ADE) and the Institution of Engineers (I) award. She has a patent for her work on mobile agent development, from the Government of India. She has also authored a book titled Mobile Computing—Theory & Practice, published by Pearson Education. Dr. Garg is Senior Member of IEEE, Fellow of Institution of Engineers (I), and Life Member of various professional societies. She has more than 47 years of experience in teaching and research and has over 135 research papers/publications in international and national journals and conferences.
Kwok Tai Chui received a BE in electronic and communication engineering with a business intelligence minor and PhD in electronic engineering from City University of Hong Kong. He has industry experience as a senior data scientist in an IoT company. He is with the Department of Technology, School of Science and Technology, at Hong Kong Metropolitan University as an assistant professor. He has more than 90 research publications, including edited books, book chapters, journal papers, and conference papers. He has served in various editorial positions in ESCI/SCIE-listed journals, including managing editor of the International Journal on Semantic Web and Information Systems, topic editor of Sensors, and associate editor of the International Journal of Energy Optimization and Engineering. His research interests include computational intelligence, data science, energy monitoring and management, intelligent transportation, smart metering, healthcare, machine learning algorithms, and optimization.
