During the seminar, the results of a research project focused on generating realistic Zigbee network traffic using a Large Language Model (LLM), specifically OpenAI's GPT-4.1, will be presented. Unlike traditional rule-based or statistical approaches, the proposed method extracts representative packet samples from real Zigbee traffic.

It incorporates sample-based learning, human-in-the-loop feedback, and prompt engineering. The presentation will include two key experiments: