RPL Attack Detection in IoT Environments: An Ensemble Approach

Ashley Etheridge, Vaibhav Anu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of IEMTRONICS 2024 - International IoT, Electronics and Mechatronics Conference
EditorsPhillip G. Bradford, S. Andrew Gadsden, Shiban K. Koul, Kamakhya Prasad Ghatak
PublisherSpringer Science and Business Media Deutschland GmbH
Pages113-122
Number of pages10
ISBN (Print)9789819747832
DOIs
StatePublished - 2025
EventInternational IoT, Electronics and Mechatronics Conference, IEMTRONICS 2024 - London, United Kingdom
Duration: 3 Apr 20245 Apr 2024

Publication series

NameLecture Notes in Electrical Engineering
Volume1228
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational IoT, Electronics and Mechatronics Conference, IEMTRONICS 2024
Country/TerritoryUnited Kingdom
CityLondon
Period3/04/245/04/24

Keywords

  • DoS
  • Ensemble method
  • IoT
  • ML
  • RPL

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