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Unsupervised Feature Selection for Outlier Detection on Streaming Data to Enhance Network Security

Over the past couple of years, machine learning methods—especially the outlier detection ones—have anchored in the cybersecurity field to detect network-based anomalies rooted in novel attack patterns. However, the ubiquity of massive continuously generated data streams poses an enormous challenge t...

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Principais autores: Michael Heigl, Enrico Weigelt, Dalibor Fiala, Martin Schramm
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI AG 2021-12-01
coleção:Applied Sciences
Assuntos:
feature selection
outlier detection
intrusion detection
network security
machine learning
online learning
Acesso em linha:https://www.mdpi.com/2076-3417/11/24/12073
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