Big Data Analytics in Fog-Enabled IoT Networks

The integration of fog computing with the resource-limited Internet of Things (IoT) network formulates the concept of the fog-enabled IoT system. Due to a large number of IoT devices, the IoT is a main source of Big Data. A large volume of sensing data is generated by IoT systems such as smart cities and smart-grid applications. A fundamental research issue is how to provide a fast and efficient data analytics solution for fog-enabled IoT systems. Big Data Analytics in Fog-Enabled IoT Networks: Towards a Privacy and Security Perspective focuses on Big Data analytics in a fog-enabled-IoT system and provides a comprehensive collection of chapters that touch on different issues related to healthcare systems, cyber-threat detection, malware detection, and the security and privacy of IoT Big Data and IoT networks. This book also emphasizes and facilitates a greater understanding of various security and privacy approaches using advanced artificial intelligence and Big Data technologies such as machine and deep learning, federated learning, blockchain, and edge computing, as well as the countermeasures to overcome the vulnerabilities of the fog-enabled IoT system.

Dr. Govind P. Gupta received his PhD degree in Computer Science & Engineering from the Indian Institute of Technology, Roorkee, India. He is currently working as an Assistant Professor in Department of Information Technology, National Institute of Technology, Raipur, India. He has made practical and theoretical contributions in Big Data Processing & Analytics, WSN, IoT and Cyber Security domains and his research has a high impact on Big data analytics, WSN, IoT, information and network security against cyber-attacks. He has published more than 50 research papers in reputed peer-reviewed Journals/Conferences including IEEE, Elsevier, ACM, Springer, Wiley, Inderscience, etc. 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, Springer Wireless Networks etc. His current research interests include Internet of Things, IoT Security, Software-defined Networking, Network Security, Big IoT Data Analytics, Blockchain-based Application development for IoT, Enterprise Blockchain. He is a professional member of the IEEE and ACM. Dr. Rakesh Tripathi received his Ph.D. degree in computer science and engineering from the Indian Institute of Technology Guwahati, India. He is an Assistant Professor with the Department of Information Technology, National Institute of Technology, Raipur, India. He has over ten years of experience in academia. He has published over 20 referred article and served as a Reviewer of several journals. His research interests include Mobile-Ad hoc Networks, Sensor Networks, Data Center Networks, Distributed Systems, Network Security, Blockchain, and Game Theory in Networks. He is a Senior member of the IEEE. Dr. Brij B. Gupta received a PhD degree from the Indian Institute of Technology, Roorkee, India, in the area of information and cyber security. He has published more than 200 research papers in international journals and conferences of high repute including IEEE, Elsevier, ACM, Springer, Wiley, Taylor & Francis Group, Inderscience, etc. He has visited several countries, i.e., Canada, Japan, the United States, the United Kingdom, Malaysia, Australia, Thailand, China, Hong Kong, Italy, Spain, etc. to present his research work. His biography was selected and published in the 30th Edition of Marquis Who's Who in the World, 2012. Dr. Gupta also received the Young Faculty Research Fellowship award from the Ministry of Electronics and Information Technology, Government of India in 2018. He is also working as a principal investigator of various research and development projects. He is serving as an associate editor of IEEE Access, IEEE TII, and the executive editor of IJITCA, Inderscience, respectively. At present, Dr. Gupta is working as an assistant professor in the Department of Computer Engineering, National Institute of Technology, Kurukshetra, India. His research interests include information security, cyber security, mobile security, cloud computing, web security, intrusion detection, and phishing. Dr. Kwok Tai Chui received the B.Eng. degree in electronic and communication engineering - Business Intelligence Minor and Ph.D. degree in electronic engineering from City University of Hong Kong. He had industry experience as Senior Data Scientist in Internet of Things (IoT) company. He is with the Department of Technology, School of Science and Technology, at Hong Kong Metropolitan University as Assistant Professor. He has more than 90 research publications including edited books, book chapters, journal papers, and conference papers. He has served as various editorial position in ESCI/SCIElisted journals including Managing Editor of International Journal on Semantic Web and Information Systems, Topic Editor of Sensors, Associate Editor of 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.

1. Deep Learning Techniques in Big Data-Enabled Internet-of-Things Devices. 2. IoMT based Smart Health Monitoring: The Future of HealthCare. 3. A Review on Intrusion Detection Systems and Cyber Threat Intelligence for Secure IoT-Enabled Network: Challenges and Directions. 4. Self-Adaptive Application Monitoring for Decentralized Edge Frameworks. 5. Federated Learning and Its Application in Malware Detection. 6. An Ensemble XGBoost Approach for the Detection of Cyber-Attacks in the Industrial IOT Domain. 7. A Review on IoT for the Application of Energy, Environment, and Waste Management: System Architecture and Future Directions. 8. Analysis of Feature Selection Methods for Android Malware Detection Using Machine Learning Techniques. 9. An Efficient Optimizing Energy Consumption Using Modified Bee Colony Optimization in Fog and IoT Networks.