Improving the Classification Effectiveness of Intrusion Detection by Using Improved Conditional Variational AutoEncoder and Deep Neural Network

Intrusion detection systems play an important role in preventing security threats and protecting networks from attacks. However, with the emergence of unknown attacks and imbalanced samples, traditional machine learning methods suffer from lower detection rates and higher false positive rates. We pr...

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Vydáno v:	Sensors (Basel, Switzerland) Ročník 19; číslo 11; s. 2528
Hlavní autoři:	Yang, Yanqing, Zheng, Kangfeng, Wu, Chunhua, Yang, Yixian
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland MDPI AG 02.06.2019 MDPI
Témata:	Artificial intelligence deep neural network generator network improved conditional variational autoencoder Internet of Things intrusion detection Intrusion detection systems Neural networks variational inference Beijing China Canada Netherlands China intrusion detection improved conditional variational autoencoder variational inference deep neural network generator network
ISSN:	1424-8220, 1424-8220
On-line přístup:	Získat plný text
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