Anomaly Detection from Log Files Using Unsupervised Deep Learning

Sathya Buršić; Vittorio Cuculo; Alessandro D’Amelio

doi:10.1007/978-3-030-54994-7_15

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Anomaly Detection from Log Files Using Unsupervised Deep Learning

Sathya Buršić Vittorio Cuculo Alessandro D’Amelio

Year: 2020 Lecture notes in computer science Pages: 200-207 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-030-54994-7_15

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Keywords:

Computer science Autoencoder Preprocessor Artificial intelligence Classifier (UML) Anomaly detection Deep learning Raw data Context (archaeology) Feature extraction Data pre-processing Binary classification Pattern recognition (psychology) Data mining Machine learning

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9.21

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Refs

0.98

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Citation History

Topics

Software System Performance and Reliability

Physical Sciences → Computer Science → Computer Networks and Communications

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Anomaly Detection from Log Files Using Unsupervised Deep Learning

Metrics

Citation History

Topics

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