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A Review of Insider Threat Detection: Classification, Machine Learning Techniques, Datasets, Open Ch...

A Review of Insider Threat Detection: Classification, Machine Learning Techniques, Datasets, Open Ch...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_4f9d4ed238404f9789242c7b402c9d8c

A Review of Insider Threat Detection: Classification, Machine Learning Techniques, Datasets, Open Challenges, and Recommendations

About this item

Full title

A Review of Insider Threat Detection: Classification, Machine Learning Techniques, Datasets, Open Challenges, and Recommendations

Publisher

Basel: MDPI AG

Journal title

Applied sciences, 2020-08, Vol.10 (15), p.5208

Language

English

Formats

Publication information

Publisher

Basel: MDPI AG

More information

Scope and Contents

Contents

Insider threat has become a widely accepted issue and one of the major challenges in cybersecurity. This phenomenon indicates that threats require special detection systems, methods, and tools, which entail the ability to facilitate accurate and fast detection of a malicious insider. Several studies on insider threat detection and related areas in...

Alternative Titles

Full title

A Review of Insider Threat Detection: Classification, Machine Learning Techniques, Datasets, Open Challenges, and Recommendations

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_4f9d4ed238404f9789242c7b402c9d8c

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_4f9d4ed238404f9789242c7b402c9d8c

Other Identifiers

ISSN

2076-3417

E-ISSN

2076-3417

DOI

10.3390/app10155208

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