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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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 19; no. 11; p. 2528
Main Authors:	Yang, Yanqing, Zheng, Kangfeng, Wu, Chunhua, Yang, Yixian
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 02.06.2019 MDPI
Subjects:	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
Online Access:	Get full text
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