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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Veröffentlicht in:	IEEE access Jg. 6; S. 41238 - 41248
Hauptverfasser:	Yan, Binghao, Han, Guodong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.01.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Anomaly detection Classification Classifiers Communications traffic Deep learning Feature extraction Intrusion detection Intrusion detection systems Machine learning Machine learning algorithms Representations Research methodology SSAE
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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