Identification of botnet attacks using hybrid machine learning models

Pandey, Amritanshu, Thaseen, Sumaiya, Aswani Kumar, Ch. and Li, Gang 2020, Identification of botnet attacks using hybrid machine learning models, in HIS 2019 : Proceedings of the 19th International Conference on Hybrid Intelligent Systems, Springer Cham, Cham, Switzerland, pp. 249-257, doi: 10.1007/978-3-030-49336-3_25.

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Title Identification of botnet attacks using hybrid machine learning models
Author(s) Pandey, Amritanshu
Thaseen, Sumaiya
Aswani Kumar, Ch.
Li, GangORCID iD for Li, Gang orcid.org/0000-0003-1583-641X
Conference name HIS 2019 Hybrid Intelligent Systems. International Conference (19th : 2019 : Bhopal, India)
Conference location Bhopal, India
Conference dates 10 - 12 Dec. 2019
Title of proceedings HIS 2019 : Proceedings of the 19th International Conference on Hybrid Intelligent Systems
Editor(s) Abraham, Ajith
Shandilya, Shishir K.
Garcia-Hernandez, Laura
Varela, Maria Leonilde
Publication date 2020
Series Advances in Intelligent Systems and Computing
Start page 249
End page 257
Total pages 9
Publisher Springer Cham
Place of publication Cham, Switzerland
Keyword(s) accuracy
botnet
clasifier
feature
phishing
CORE2018 C
CORE2020 C
Notes Abbreviations IDS - Intrusion Detection System KNN- K-Nearest Neighbor LR - Linear Regression NB - Naïve Bayes RF - Random Forest SVM - Support Vector Machine This paper is an extension of Khan N.M., Madhav C. N., Negi A., Thaseen I.S. (2020) Analysis on Improving the Performance of Machine Learning Models Using Feature Selection Technique. In: Abraham A., Cherukuri A., Melin P., Gandhi N. (eds) Intelligent Systems Design and Applications.
ISBN 9783030493356
ISSN 2194-5357
2194-5365
Language eng
DOI 10.1007/978-3-030-49336-3_25
Indigenous content off
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2021, The Editors (if applicable) and The Authors
Persistent URL http://hdl.handle.net/10536/DRO/DU:30141457

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