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IEEE/ICACT20210225 Slide.12        [Big Slide]	Oral Presentation
	Building a successful machine learning model that can recognize cyber threats requires large amounts of training data. Building labeled datasets for 5G network security is significant and essential. Therefore, we collected network data from the 5G-based real smart-factory to build the datasets. Subsequently, we replayed the traffic on the 5G testbed that we built and re-collected the generated traffic. ~~~ We implemented modified packets on the 5G testbed which comprised a user terminal composed of N virtual machines, a 5GC, and a gNB that replayed normal and abnormal data collected based on the 5G network. Subsequently, the data generated in the testbed were re-collected by the collector. By repeating collection and replay, a dataset for AI-based intrusion detection was created.

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