AI Enabled Learning Architecture Using Network Traffic Traces over IoT Network

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Abstract: This research describes IoT device testbeds to collect network traffic in a local area network and cyberspace, including traffic traces beyond 5G/6G at different layers. We also describe research problems and challenges, such as traffic classification and traffic prediction by the traffic traces of devices. An AI-enabled hierarchical learning architecture for the problems above using sources like network packets, frames, and signals from the traffic traces with machine learning models is also presented.