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Journal article
Machine Learning Based Intrusion Detection for IoT Botnet
International journal of machine learning and computing, Vol.11(6), pp.399-406
11/2021
Abstract
In this article, we analyzed botnet traffic in an IoT environment using three machine learning classifiers: Logistic Regression, Support-Vector Machine and Random Forest. We classified each attack in each botnet for nine devices. We calculated the Accuracy, True Positive, False Positive, False Negative, True Negative, Precision, Recall, F1 score for each algorithm. We obtained impressive results (above 99%) using these three classifiers. We have a high attack detection rate. A brief analysis of the results is presented.
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- Title
- Machine Learning Based Intrusion Detection for IoT Botnet
- Publication Details
- International journal of machine learning and computing, Vol.11(6), pp.399-406
- Resource Type
- Journal article
- Publisher
- International Association of Computer Science and Information Technology (I A C S I T)
- Copyright
- Copyright © 2021 by the authors.
- Identifiers
- 99380178994606600
- Academic Unit
- Mathematics and Statistics; Computer Science; Hal Marcus College of Science and Engineering
- Language
- English