Intrusion Detection of Imbalanced Network Traffic Based on Machine Learning and Deep Learning

Intrusion Detection of Imbalanced Network Traffic Based on Machine Learning and Deep Learning

In imbalanced network traffic, malicious cyber-attacks can often hide in large amounts of normal data. It exhibits a high degree of stealth and obfuscation in cyberspace, making it difficult for Network Intrusion Detection System(NIDS) to ensure the accuracy and timeliness of detection. This paper r...

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Bibliographic Details
Main Authors: Lan Liu, Pengcheng Wang, Jun Lin, Langzhou Liu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
IDS
imbalanced network traffic
machine learning
deep learning
CSE-CIC-IDS2018
Online Access:https://ieeexplore.ieee.org/document/9311173/

Internet

https://ieeexplore.ieee.org/document/9311173/

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