AutoLog: Anomaly detection by deep autoencoding of system logs

The use of system logs for detecting and troubleshooting anomalies of production systems has been known since the early days of computers. In spite of the advances in the area, the analysis of log files emitted by real-life systems poses many peculiar challenges. Up-to-date tools, such as log manage...

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Veröffentlicht in:	Expert systems with applications Jg. 191; S. 116263
Hauptverfasser:	Catillo, Marta, Pecchia, Antonio, Villano, Umberto
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Elsevier Ltd 01.04.2022 Elsevier BV
Schlagworte:	Anomalies Anomaly detection Autoencoder Comparative studies Cybersecurity Data logging Decision trees Deep learning Information management Standard data System logs Troubleshooting Deep learning Cybersecurity Autoencoder System logs Anomaly detection
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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