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To address the existing problem, we proposed a novel method and system for generating training data to support AI-based anomaly detection. Our approach is grounded in collecting real-world network traffic data, offering a distinct advantage in accurately reflecting the unique characteristics of the network under consideration. Furthermore, our system is designed to incorporate data related to the latest malicious attacks within the network, ensuring that AI-based anomaly detection methods are well-equipped to handle the dynamic nature of cybersecurity threats.
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IEEE/ICACT20240309 Slide.04
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