1. Brunel University Research Archive
  2. College of Engineering, Design and Physical Sciences
  3. Dept of Electronic and Electrical Engineering
  4. Dept of Electronic and Electrical Engineering Research Papers
Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/17747
Full metadata record
DC FieldValueLanguage
dc.contributor.authorYao, H-
dc.contributor.authorFu, D-
dc.contributor.authorZhang, P-
dc.contributor.authorLi, M-
dc.contributor.authorLiu, Y-
dc.date.accessioned2019-03-20T14:02:06Z-
dc.date.available2018-10-01-
dc.date.available2019-03-20T14:02:06Z-
dc.date.issued2018-10-01-
dc.identifier.citationIEEE Internet of Things Journal, 2018, pp. 1 - 11en_US
dc.identifier.issn2327-4662-
dc.identifier.issnhttp://dx.doi.org/10.1109/JIOT.2018.2873125-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/17747-
dc.format.extent1 - 11-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectintrusion detectionen_US
dc.subjectsemi-supervised learningen_US
dc.subjectunknown pattern discoveryen_US
dc.subjectclass imbalanceen_US
dc.subjectnon-identical distributionen_US
dc.titleMSML: A Novel Multi-level Semi-supervised Machine Learning Framework for Intrusion Detection Systemen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1109/JIOT.2018.2873125-
dc.relation.isPartOfIEEE Internet of Things Journal-
pubs.publication-statusAccepted-
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

Files in This Item:
File Description SizeFormat 
FullText.pdf1.16 MBAdobe PDFView/Open
Show simple item record


Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.