Botnet Classification using Machine Learning

Botnet is one of the cyber security threats which may cause big damages. This research uses Machine Learning methods to classify and then detect botnet attacks. The CTU-13 dataset is used, and 90,962 records are trained in a 3-layer Deep Learning sequential model. The result has 99% accuracy and the value of recall, precision and F1 score is 99% as well.

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Published
2024-08-19
DOI
https://doi.org/10.1109/isocc62682.2024.10762399
Primary Topic
Network Security and Intrusion Detection
Type
article
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article

Botnet Classification using Machine Learning

Man Ni, Gabriela Mogos
Network Security and Intrusion Detection
article

Botnet Classification using Machine Learning

Man Ni, Gabriela Mogos
article en

Abstract

Botnet is one of the cyber security threats which may cause big damages. This research uses Machine Learning methods to classify and then detect botnet attacks. The CTU-13 dataset is used, and 90,962 records are trained in a 3-layer Deep Learning sequential model. The result has 99% accuracy and the value of recall, precision and F1 score is 99% as well.

Xi’an Jiaotong-Liverpool University (CN)
Openalex Percentile: Top 75%
Network Security and Intrusion Detection
DOISourceOpenAlex
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Botnet Classification using Machine Learning — Man Ni, Gabriela Mogos · (2024) | TGRS Research Map | TGRS