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November 16, 2025Indian Journal of Science and TechnologyOpen Access

IoT Botnet Detection: A Comparative Performance Analysis of Various ML Models on IoT-23 Dataset

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Authors

RDRintu DasVDVaskar DekaGTGom Taye

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Overview

This analysis reveals that Decision Tree achieved 99.99% accuracy in botnet detection, indicating it may be optimal for real-time IoT applications.

Key Points

  • Precision, Recall, and F1-score all reached 99.99% with Decision Tree, Random Forest, and K-Nearest Neighbors.
  • Support Vector Machine and Logistic Regression showed moderate accuracy levels at 64.31% and 72.65%, respectively.
  • Principal Component Analysis and SMOTE balancing were used for feature optimization and class imbalance handling.
  • Latency for Decision Tree was only 0.0837 seconds, making it suitable for constrained IoT devices.

Cite This Study

Das et al. (2025) studied this question.

synapsesocial.com/papers/692509ffc0ce034ddc3531dfhttps://doi.org/10.17485/ijst/v18i41.974
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