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While AI-based anomaly detection is gaining widespread attention and application, the reliance on open datasets for research and testing has certain limitations. Existing open datasets, collected from specific networks, may not be directly applicable to other network environments due to variations in normal and malicious packet behaviors. As a solution, we have proposed a system that collects packets directly from live networks, produced a more accurate representation of the network's unique characteristics. This approach to data collection not only enhances the performance of AI-based anomaly detection but also contributes to the ongoing development of more adaptable systems.
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IEEE/ICACT20240309 Slide.21
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