An efficient XGBoost–DNN-based classification model for network intrusion detection system
An efficient XGBoost–DNN-based classification model for network intrusion detection system
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Author / Creator
Publisher
London: Springer London
Journal title
Language
English
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Publisher
London: Springer London
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Scope and Contents
Contents
There is a steep rise in the trend of the utility of Internet technology day by day. This tremendous increase ushers in a massive amount of data generated and handled. For apparent reasons, undivided attention is due for ensuring network security. An intrusion detection system plays a vital role in the field of the stated security. The proposed XGB...
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Full title
An efficient XGBoost–DNN-based classification model for network intrusion detection system
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Record Identifier
TN_cdi_proquest_journals_2426703407
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2426703407
Other Identifiers
ISSN
0941-0643
E-ISSN
1433-3058
DOI
10.1007/s00521-020-04708-x
