Detecting Version Number Attacks in Low Power and Lossy Networks for Internet of Things Routing: Review and Taxonomy

Anbar, Mohammed, Momani, A M, Alfriehat, Nadia A., Karuppayah, Shankar, Rihan, Shaza Dawood Ahmed and Alabsi, Basim Ahmad (2024) Detecting Version Number Attacks in Low Power and Lossy Networks for Internet of Things Routing: Review and Taxonomy. IEEE Access, 12. pp. 31136-31158. ISSN 2169-3536

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Abstract

The internet of things (IoT) is an emerging technological advancement with significantimplications. It connects a wireless sensor or node network via low-power and lossy networks (LLN). Therouting protocol over a low-power and lossy network (RPL) is the fundamental component of LLN. Itslightweight design effectively addresses the limitations imposed by bandwidth, energy, and memory on bothLLNs and IoT devices. Notwithstanding its efficacy, RPL introduces susceptibilities, including the versionnumber attack (VNA), which underscores the need for IoT systems to implement effective security protocols.This work reviews and categorizes the security mechanisms proposed in the literature to detect VNA againstRPL-based IoT networks. The existing mechanisms are thoroughly discussed and analyzed regarding theirperformance, datasets, implementation details, and limitations. Furthermore, a qualitative comparison ispresented to benchmark this work against existing studies, showcasing its uniqueness. Finally, this workanalyzes research gaps and proposes future research avenues.

Affiliation: Skyline University College
SUC Author(s): Anbar, Mohammed and Momani, A M ORCID: https://orcid.org/0000-0002-6764-6186
All Author(s): Anbar, Mohammed, Momani, A M, Alfriehat, Nadia A., Karuppayah, Shankar, Rihan, Shaza Dawood Ahmed and Alabsi, Basim Ahmad
Item Type: Article
Uncontrolled Keywords: IoT, RPL protocol, VNA, intrusion detection system, security, LLN
Subjects: B Information Technology > BP Internet of Things
Divisions: Skyline University College > School of IT
Depositing User: Mr Mosys Team
Date Deposited: 25 Apr 2024 16:28
Last Modified: 25 Apr 2024 16:28
URI: https://research.skylineuniversity.ac.ae/id/eprint/861
Publisher URL: https://doi.org/10.1109/ACCESS.2024.3368633
Publisher OA policy: https://v2.sherpa.ac.uk/id/publication/24685
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