Characterizing the Impact of Data-Damaged Models on Generalization Strength in Intrusion Detection

Characterizing the Impact of Data-Damaged Models on Generalization Strength in Intrusion Detection

Generalization is a longstanding assumption in articles concerning network intrusion detection through machine learning. Novel techniques are frequently proposed and validated based on the improvement they attain when classifying one or more of the existing datasets. The necessary follow-up question...

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Bibliographic Details
Main Authors: Laurens D’hooge, Miel Verkerken, Tim Wauters, Filip De Turck, Bruno Volckaert
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Journal of Cybersecurity and Privacy
Subjects:
intrusion detection
network security
supervised machine learning
generalization strength
CIC-IDS2017
CSE-CIC-IDS2018
Online Access:https://www.mdpi.com/2624-800X/3/2/8

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