Detecting Unbalanced Network Traffic Intrusions With Deep Learning
The growth of cyber threats demands a robust and adaptive intrusion detection system (IDS) capable of effectively recognizing malicious activities from network traffic. However, the existing imbalance of class in network data possesses a significant challenge to traditional IDS. To overcome these ch...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10538232/ |