Cloud-based multiclass anomaly detection and categorization using ensemble learning
Cloud-based multiclass anomaly detection and categorization using ensemble learning
About this item
Full title
Author / Creator
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
Formats
Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Subjects
More information
Scope and Contents
Contents
The world of the Internet and networking is exposed to many cyber-attacks and threats. Over the years, machine learning models have progressed to be integrated into many scenarios to detect anomalies accurately. This paper proposes a novel approach named cloud-based anomaly detection (
CAD
) to detect cloud-based anomalies.
CAD
consist...
Alternative Titles
Full title
Cloud-based multiclass anomaly detection and categorization using ensemble learning
Authors, Artists and Contributors
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Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_acd82103d8804cd9a1474183d282490b
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_acd82103d8804cd9a1474183d282490b
Other Identifiers
ISSN
2192-113X
E-ISSN
2192-113X
DOI
10.1186/s13677-022-00329-y
