A Novel Wireless Network Intrusion Detection Method Based on Adaptive Synthetic Sampling and an Improved Convolutional Neural Network

A Novel Wireless Network Intrusion Detection Method Based on Adaptive Synthetic Sampling and an Improved Convolutional Neural Network

The diversity of network attacks poses severe challenges to intrusion detection systems (IDSs). Traditional attack recognition methods usually adopt mining data associations to identify anomalies, which has the disadvantages of a high false alarm rate (FAR), low recognition accuracy (ACC) and poor g...

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Bibliographic Details
Main Authors: Zhiquan Hu, Liejun Wang, Lei Qi, Yongming Li, Wenzhong Yang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Intrusion detection
adaptive synthetic sampling
AS-CNN
NSL-KDD
Online Access:https://ieeexplore.ieee.org/document/9239970/

Internet

https://ieeexplore.ieee.org/document/9239970/

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