AREP: an adaptive, machine learning-based algorithm for real-time anomaly detection on network telemetry data

Abnormal behaviour detection is an essential task of real-time monitoring to secure the reliable operation of ICT infrastructures. This paper presents AREP, an adaptive, long short-term memory-based machine learning algorithm for real-time anomaly detection on network telemetry data. AREP is an impr...

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Veröffentlicht in:	Neural computing & applications Jg. 35; H. 8; S. 6079 - 6094
1. Verfasser:	Farkas, Karoly
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.03.2023 Springer Nature B.V
Schlagworte:	Adaptive algorithms Algorithms Anomalies Artificial Intelligence Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Identification methods Image Processing and Computer Vision Machine learning Original Article Performance evaluation Probability and Statistics in Computer Science Real time Telemetry Time series Network telemetry AREP LSTM Anomaly detection Machine learning Time series
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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