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Full Description
Artificial intelligence (AI) and its applications have risen to prominence as one of the most active study areas in recent years. In recent years, a rising number of AI applications have been applied in a variety of areas. Agriculture, transportation, medicine, and health are all being transformed by AI technology. The Internet of Things (IoT) market is thriving, having a significant impact on a wide variety of industries and applications, including e-health care, smart cities, smart transportation, and industrial engineering. Recent breakthroughs in artificial intelligence and machine learning techniques have reshaped various aspects of artificial vision, considerably improving the state of the art for artificial vision systems across a broad range of high-level tasks. As a result, several innovations and studies are being conducted to improve the performance and productivity of IoT devices across multiple industries using machine learning and artificial intelligence. Security is a primary consideration when analyzing the next generation communication network due to the rapid advancement of technology. Additionally, data analytics, deep intelligence, deep learning, cloud computing, and intelligent solutions are being employed in medical, agricultural, industrial, and health care systems that are based on the Internet of Things. This book will look at cutting-edge Network Attacks and Security solutions that employ intelligent data processing and Machine Learning (ML) methods.
This book:
Covers emerging technologies of network attacks and management aspects
Presents artificial intelligence techniques for networks and resource optimization, and toward network automation, and security
Showcases recent industrial and technological aspects of next-generation networks
Illustrates artificial intelligence techniques to mitigate cyber-attacks, authentication, and authorization challenges
Explains smart, and real-time monitoring services, multimedia, cloud computing, and information processing methodologies in 5G networks
It is primarily for senior undergraduates, graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology
Contents
1. Enhancing 5G and IoT Network Security: A Multi-Model Deep Learning Approach for Attack Classification. 2. Dynamic Deployment and Traffic Scheduling of UPF in 5G Networks. 3. Spatial Federated Learning and Blockchain based 5G Communication Model for Hiding Confidential Information. 4. Mining Intelligence Hierarchical Feature for Malware Detection over 5G Network. 5. Enhancing Reliability and Security of Power Monitoring Systems in the Era of 5G Networks. 6. Passive Voice in 5G Mobile Edge Computing: Optimizing Energy Efficiency and Resource Utilization. 7. Exchange Matching Algorithm for Low-Complexity Traffic Scheduling for 5G Fronthaul Networks. 8. Attack Path Discovery in Dynamic Network Environments for Automated Penetration Testing over 5G Networks. 9. Enhancing Electric Vehicle Charging Efficiency in Urban Areas with 5G Network Integration and Network Attack Mitigation. 10. Next-Generation Intrusion Detection System for 5G Networks with Enhanced Security Using Updated Datasets
