Analytical Study of Local Repair Attack on RPL-Based 6LoWPAN Networks in Internet of Things

Hussah Albinali, Rakan Alghofaili, Farag Azzedin

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

2 Scopus citations

Abstract

RPL was developed as a routing protocol in low-power and lossy network contexts to connect many applications using IP-based communication. However, RPL has been exploited to launch several attacks, including local repair attacks. we have evaluated the effect of the local repair attack on the network performance and compared it with the normal RPL. We have conducted simulations on different topologies that included grid and binary topology. The results obtained show that the local repair attack affects the performance of the RPL protocol. The drop in PDR has severely impacted the binary topology to reach only 82%. Moreover, the grid topology suffers from E2E delay, which increases by 50% to reach an average of 2.2 seconds. In addition, the grid topology consumes approximately 40% additional power when the network is under local repair attacks.

Original languageEnglish
Title of host publicationICFNDS 2023 - 2023 The 7th International Conference on Future Networks and Distributed Systems
PublisherAssociation for Computing Machinery
Pages641-646
Number of pages6
ISBN (Electronic)9798400709036
DOIs
StatePublished - 21 Dec 2023
Event7th International Conference on Future Networks and Distributed Systems, ICFNDS 2023 - Dubai, United Arab Emirates
Duration: 21 Dec 202322 Dec 2023

Publication series

NameACM International Conference Proceeding Series

Conference

Conference7th International Conference on Future Networks and Distributed Systems, ICFNDS 2023
Country/TerritoryUnited Arab Emirates
CityDubai
Period21/12/2322/12/23

Bibliographical note

Publisher Copyright:
© 2023 ACM.

Keywords

  • IoT
  • Local repair
  • Rank attack
  • Routing attack
  • RPL

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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