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Bridging the Last-Mile Gap in Network Security via Generating Intrusion-Specific Detection Patterns through Machine Learning
2022
Security and Communication Networks
With successful machine learning applications in many fields, researchers tried to introduce machine learning into intrusion detection systems for building classification models. Although experimental results showed that these classification models could produce higher accuracy in predicting network attacks on the offline datasets, compared with the operational intrusion detection systems, machine learning is rarely deployed in the real intrusion detection environment. This is what we call the
doi:10.1155/2022/3990386
fatcat:3a5ry6k2uzfk5o6motlbhpz2yq