A Trust-Based Intrusion Detection System for RPL Networks: Detecting a Combination of Rank and Blackhole Attacks

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Abstract

Routing attacks are a major security issue for Internet of Things (IoT) networks utilising routing protocols, as malicious actors can overwhelm resource-constrained devices with denial-of-service (DoS) attacks, notably rank and blackhole attacks. In this work, we study the impact of the combination of rank and blackhole attacks in the IPv6 routing protocol for low-power and lossy (RPL) networks, and we propose a new security framework for RPL-based IoT networks (SRF-IoT). The framework includes a trust-based mechanism that detects and isolates malicious attackers with the help of an external intrusion detection system (IDS). Both SRF-IoT and IDS are implemented in the Contiki-NG operating system. Evaluation of the proposed framework is based on simulations using the Whitefield framework that combines both the Contiki-NG and the NS-3 simulator. Analysis of the simulations of the scenarios under active attacks showed the effectiveness of deploying SRF-IoT with 92.8% packet delivery ratio (PDR), a five-fold reduction in the number of packets dropped, and a three-fold decrease in the number of parent switches in comparison with the scenario without SRF-IoT. Moreover, the packet overhead introduced by SRF-IoT in attack scenarios is minimal at less than 2%. Obtained results suggest that the SRF-IoT framework is an efficient and promising solution that combines trust-based and IDS-based approaches to protect IoT networks against routing attacks. In addition, our solution works by deploying a watchdog mechanism on detector nodes only, leaving unaffected the operation of existing smart devices.
Original languageEnglish
Pages (from-to)124-153
JournalJournal of Cybersecurity and Privacy
Volume2
Issue number1
DOIs
Publication statusPublished - 9 Mar 2022

Bibliographical note

© 2022 by the authors.
Licensee MDPI, Basel, Switzerland

Keywords

  • RPL security
  • Intrusion detection and prevention system

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