Effective Feature Extraction via Stacked Sparse Autoencoder to Improve Intrusion Detection System

Effective Feature Extraction via Stacked Sparse Autoencoder to Improve Intrusion Detection System

Classification features are crucial for an intrusion detection system (IDS), and the detection performance of IDS will change dramatically when providing different input features. Moreover, the large number of network traffic and their high-dimensional features will result in a very lengthy classifi...

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Bibliographic Details
Main Authors: Binghao Yan, Guodong Han
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Intrusion detection
deep learning
machine learning
SSAE
feature extraction
Online Access:https://ieeexplore.ieee.org/document/8418451/

Internet

https://ieeexplore.ieee.org/document/8418451/

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