Real-time anomaly detection based on long short-Term memory and Gaussian Mixture Model

Anomaly detection is a long-standing problem in system designation. High-quality anomaly detection can benefit plenty of applications (e.g. system monitoring, disaster precaution and intrusion detection). Most of the existing anomalies detection algorithms are less competent for both effectiveness a...

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Veröffentlicht in:	Computers & electrical engineering Jg. 79; S. 106458
Hauptverfasser:	Ding, Nan, Ma, HaoXuan, Gao, Huanbo, Ma, YanHua, Tan, GuoZhen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier Ltd 01.10.2019 Elsevier BV
Schlagworte:	Algorithms Anomalies Anomaly detection Datasets Gaussian mixture model Intrusion Long short term memory Multivariate sensing time series Probabilistic models Real time Short term Multivariate sensing time series Anomaly detection Long short term memory Gaussian mixture model
ISSN:	0045-7906, 1879-0755
Online-Zugang:	Volltext
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