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An Adaptive Behavioral-Based Incremental Batch Learning Malware Variants Detection Model Using Concept Drift Detection and Sequential Deep Learning

Darem, AA, Ghaleb, FA, Al-Hashmi, AA, Abawajy, Jemal, Alanazi, SM and Al-Rezami, AY 2021, An Adaptive Behavioral-Based Incremental Batch Learning Malware Variants Detection Model Using Concept Drift Detection and Sequential Deep Learning, IEEE Access, vol. 9, pp. 97180-97196, doi: 10.1109/ACCESS.2021.3093366.

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Title An Adaptive Behavioral-Based Incremental Batch Learning Malware Variants Detection Model Using Concept Drift Detection and Sequential Deep Learning
Author(s) Darem, AA
Ghaleb, FA
Al-Hashmi, AA
Abawajy, JemalORCID iD for Abawajy, Jemal orcid.org/0000-0001-8962-1222
Alanazi, SM
Al-Rezami, AY
Journal name IEEE Access
Volume number 9
Start page 97180
End page 97196
Total pages 17
Publisher Institute of Electrical and Electronics Engineers
Place of publication Piscataway, N.J.
Publication date 2021-06-29
ISSN 2169-3536
Keyword(s) Malware variant detection
adaptive incremental batch learning
concept drift detection
deep learning
statistical process control
Language eng
DOI 10.1109/ACCESS.2021.3093366
Field of Research 08 Information and Computing Sciences
09 Engineering
10 Technology
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30154235

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.