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Supervised Feature Selection Techniques in Network Intrusion Detection: a Critical Review

By Mario Mauro and others
Machine Learning (ML) techniques are becoming an invaluable support for network intrusion detection, especially in revealing anomalous flows, which often hide cyber-threats. Typically, ML algorithms are exploited to classify/recognize data traffic on the basis of statistical features such as inter-arrival times, packets length distribution, mean number of flows, etc. Dealing... Show more
April 11, 2021
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Supervised Feature Selection Techniques in Network Intrusion Detection: a Critical Review
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