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Page 6 - Software Defined Networking News Today : Breaking News, Live Updates & Top Stories | Vimarsana

Network Automation Market size to record USD 29 02 billion growth from 2023-2027, Use of AI with network automation is one of the key market trends, Technavio

Global Edge Data Center Market Analysis Report 2023-2033: Expansion Essential for Lower Latency Services, IoT Expansion, Cloud Adoption, and 5G, & Redefining Data Processing and Connectivity

Software-Defined IoT with Machine Learning-Based Enhanced Security by Ali Husnain, Chau Nguyen et al

The widespread adoption of IoT devices has revolutionized multiple sectors, including healthcare, military, agriculture, and smart cities. This surge in IoT-generated data raises significant security concerns, necessitating efficient strategies for large-scale data analysis to safeguard IoT devices. Existing research has explored the fusion of Software-Defined Networking (SDN) and machine learning (ML), particularly flow-based monitoring, for intrusion detection. However, as IoT data volumes grow, challenges such as scalability, adaptability to new attack vectors, and resource-intensive monitoring persist. Our solution combines SD-IoT and ML to enhance IoT network security. By isolating virtual networks based on device characteristics, we improve intrusion detection efficiency and facilitate research on emerging threats. We present a real-world implementation, demonstrating a scalable and robust ML-based security for SD-IoT system.

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