Secure Edge and Fog Computing Enabled AI for IoT and Smart Cities -

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Sommaire:
Part 1: AI Enabled Smart City IoT System using Edge /Fog Computing.- Chapter 1. Multi-level edge computing system for autonomous vehicles.- Chapter 2. UAVs based edge computing system for smart city applications.- Chapter 3. Organization of Smart City Services Based on Microservice Architecture.- Chapter 4. Pseudo-Random Error-Correcting Codes in Network Coding.- Chapter 5. Proactive management in Smart City: transport convoys.- Chapter 6. Federated Learning for Linux Malware Detection: An Experimental Study.- Chapter 7. Delay prediction in M2M networks using Deep Learning approach.- Chapter 8. Energy-Efficient Beam Shaping in MIMO System Using Machine Learning.- Chapter 9. Channel Cluster Configuration Selection Method for IEEE 802.11 Networks Planning.- Chapter 10. Service migration algorithm for UAVs recharge zones in future 6G network.- Chapter 11. FedBA: Non-IID Federated Learning Framework in UAV Networks.- Part 2: Fog/Edge Computing Security Issues.- Chapter 12. Big Data Analytics for Secure Edge-based Manufacturing Internet of Things (MIoT).- Chapter 13. Artificial Intelligence-Based Secure Edge Computing Systems for IoTDs and Smart Cities: A Survey.- Chapter 14. Machine Learning Techniques for Secure Edge SDN.- Chapter 15.  Machine Learning-Based Identity and Access Management for Cloud Security.- Chapter 16. Spatial Data of Smart Cities: Trust.- Chapter 17. Smart City Infrastructure Projects: Spatial Data of Risks.- Chapter 18. A Comparative Analysis of Blockchain-Based Authentication Models for IoT Networks.- Chapter 19. Development of determining a wireless client location method in the IEEE 802.11 network in order to ensure the IT infrastructure security.