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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Vydané v:	Applied sciences Ročník 9; číslo 2; s. 238
Hlavní autori:	Yang, Yanqing, Zheng, Kangfeng, Wu, Chunhua, Niu, Xinxin, Yang, Yixian
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 10.01.2019
Predmet:	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
On-line prístup:	Získať plný text
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