Big Data Analytics in Fog-Enabled IoT Networks

This book emphasizes and facilitate a greater understanding of various security and privacy approaches using the advance AI and Big data technologies like machine/deep learning, federated learning, blockchain, edge computing and the countermeasures to overcome the vulnerabilities of the Fog-enabled IoT system.

Govind P. Gupta, Kwok Tai Chui

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.