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The Internet of Things’ rapid growth has given rise to significant security challenges. This paper addresses security concerns in IoT within Low power and Lossy Networks (LLNs) that utilize the Routing Protocol for Low Power and Lossy Networks (RPL). We propose a novel ensemble classifier, DT- NB-ANN-SGD, to detect various RPL attacks. Our experimentation compares this ensemble approach with individual classifiers (DT, NB, ANN, SGD) using the ROUT-4-2023 dataset. Results indicate promising accuracy (86.21%) but highlight the need for further improvement in recall and F1 scores. This study contributes insights for enhancing RPL attack detection in IoT environments.

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RPL Attack Detection in IoT Environments: An Ensemble Approach

  • 会议论文

  • 发表日期：

    2025年

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  • Ashley Etheridge,
  • Vaibhav Anu

摘要

The Internet of Things’ rapid growth has given rise to significant security challenges. This paper addresses security concerns in IoT within Low power and Lossy Networks (LLNs) that utilize the Routing Protocol for Low Power and Lossy Networks (RPL). We propose a novel ensemble classifier, DT- NB-ANN-SGD, to detect various RPL attacks. Our experimentation compares this ensemble approach with individual classifiers (DT, NB, ANN, SGD) using the ROUT-4-2023 dataset. Results indicate promising accuracy (86.21%) but highlight the need for further improvement in recall and F1 scores. This study contributes insights for enhancing RPL attack detection in IoT environments.