Document Type
Preprint
Publication Date
1-1-2025
Journal / Book Title
Lecture Notes in Electrical Engineering
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.
DOI
10.1007/978-981-97-4784-9_8
Journal ISSN / Book ISBN
85218441707 (Scopus)
Montclair State University Digital Commons Citation
Etheridge, Ashley and Anu, Vaibhav, "RPL Attack Detection in IoT Environments: An Ensemble Approach" (2025). School of Computing Faculty Scholarship and Creative Works. 21.
https://digitalcommons.montclair.edu/computing-facpubs/21