Robust Network Intrusion Detection System Based on Machine-Learning With Early Classification

Robust Network Intrusion Detection System Based on Machine-Learning With Early Classification

Network Intrusion Detection Systems (NIDSs) using pattern matching have a fatal weakness in that they cannot detect new attacks because they only learn existing patterns and use them to detect those attacks. To solve this problem, a machine learning-based NIDS (ML-NIDS) that detects anomalies throug...

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Bibliographic Details
Main Authors: Taehoon Kim, Wooguil Pak
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Network intrusion detection
early classification
robust classification
adversarial attack
machine-learning
Online Access:https://ieeexplore.ieee.org/document/9687553/

Internet

https://ieeexplore.ieee.org/document/9687553/

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