High-Level Defence Model against Routing Attacks on the Internet-of-Things

Authors

  • Lanka Chris Sejaphala North-West University
  • Vusi Malele North-West University
  • Francis Lugayizi North-West University

DOI:

https://doi.org/10.33022/ijcs.v13i1.3744

Keywords:

Internet of Things, RPL, Machine learning,

Abstract

This paper is part of the doctoral work that aims to answer the following research question: “To what extent can an intelligent security model effectively defend against routing attacks in RPL-based Internet of Things (IoT) with a demonstration of less network resource consumption, high detection rate, and minimal false negatives?” To answer this question, this paper proposes a high-level conceptual framework to defend the IoT against routing attacks. In recent works, mitigation techniques have been proposed to act against routing attacks, however conceptual defence or mitigation framework is not presented as a set of steps to follow to develop an effective and robust intelligent security model. This paper aims to present a high-level conceptual defence framework against routing attacks; specifically, sinkhole, rank, DIS-Flooding, and worst parent. The four mentioned routing attacks are capable of disturbing IoT network functions and operations, and consuming network resources such as memory and power.

 

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Published

01-03-2024