Building an Effective Intrusion Detection System Using the Modified Density Peak Clustering Algorithm and Deep Belief Networks

Machine learning plays an important role in building intrusion detection systems. However, with the increase of data capacity and data dimension, the ability of shallow machine learning is becoming more limited. In this paper, we propose a fuzzy aggregation approach using the modified density peak c...

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Veröffentlicht in:	Applied sciences Jg. 9; H. 2; S. 238
Hauptverfasser:	Yang, Yanqing, Zheng, Kangfeng, Wu, Chunhua, Niu, Xinxin, Yang, Yixian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 10.01.2019
Schlagworte:	Accuracy Algorithms Artificial intelligence Classification Clustering Computer networks Datasets deep belief networks Deep learning fuzzy aggregation intrusion detection Intrusion detection systems Machine learning modified density peak clustering algorithm Neural networks Principal components analysis restricted Boltzmann machine Teaching methods
ISSN:	2076-3417, 2076-3417
Online-Zugang:	Volltext
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