Learning from few cyber-attacks : addressing the class imbalance problem in machine learning-based intrusion detection in software-defined networking
author
Mirsadeghi, Seyed Mohammad Hadi
Bahsi, Hayretdin
Vaarandi, Risto
Inoubli, Wissem
statement of authorship
Seyed Mohammad Hadi Mirsadeghi, Hayretdin Bahsi, Risto Vaarandi, Wissem Inoubli
source
IEEE Access
publisher
IEEE
journal volume number month
vol. 11
year of publication
2023
pages
p. 140428 - 140442
url
https://doi.org/10.1109/ACCESS.2023.3341755
subject term
sügavõpe
tehisõpe
küberturve
arvutivõrgud
keyword
class imbalance problem
cyber intrusion detection
deep learning
machine learning
software-defined networking
ISSN
2169-3536
notes
Bibliogr.: 59 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
1.1
Scopus
https://www.scopus.com/sourceid/21100374601
https://www.scopus.com/record/display.uri?eid=2-s2.0-85179784530&origin=resultslist&sort=plf-f&src=s&sid=b809bd4cf0195b89d03fdce880010424&sot=b&sdt=b&s=TITLE%28%22Learning+From+Few+Cyber-Attacks%3A+Addressing+the+Class+Imbalance+Problem+in+Machine+Learning-Based+Intrusion+Detection+in+Software-Defined+Networking%22%29&sl=111&sessionSearchId=b809bd4cf0195b89d03fdce880010424&relpos=0
WOS
https://jcr.clarivate.com/jcr-jp/journal-profile?journal=IEEE%20ACCESS&year=2023
https://www.webofscience.com/wos/woscc/full-record/WOS:001126163700001
category (general)
Engineering
Tehnika
Computer science
Arvutiteadus
Materials science
Materjaliteadus
category (sub)
Engineering. General engineering
Tehnika. Üldine inseneriteadus
Computer science. General computer science
Arvutiteadus. Üldine arvutiteadus
Materials science. General materials science
Materjaliteadus. Üldine materjaliteadus
quartile
Q1
TalTech department
tarkvarateaduse instituut
language
inglise