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THC-RPL: A lightweight Trust-enabled routing in RPL-based IoT networks against Sybil attack

Author

Listed:
  • Danyal Arshad
  • Muhammad Asim
  • Noshina Tariq
  • Thar Baker
  • Hissam Tawfik
  • Dhiya Al-Jumeily OBE

Abstract

The Internet of Things (IoT) and its relevant advances have attracted significant scholarly, governmental, and industrial attention in recent years. Since the IoT specifications are quite different from what the Internet can deliver today, many groundbreaking techniques, such as Mobile Ad hoc Networks (MANETs) and Wireless Sensor Networks (WSN), have gradually been integrated into IoT. The Routing Protocol for Low power and Lossy network (RPL) is the de-facto IoT routing protocol in such networks. Unfortunately, it is susceptible to numerous internal attacks. Many techniques, such as cryptography, Intrusion Detection System (IDS), and authorization have been used to counter this. The large computational overhead of these techniques limits their direct application to IoT nodes, especially due to their low power and lossy nature. Therefore, this paper proposes a Trust-based Hybrid Cooperative RPL protocol (THC-RPL) to detect malicious Sybil nodes in an RPL-based IoT network. The proposed technique is compared and evaluated with state-of-the-art and is found to outperform them. It detects more attacks while maintaining the packet loss ratio in the range of 15-25%. The average energy consumption of the nodes also remains in the ratio of 60-80 mj. There is approximately 40% more energy conservation at node level with an overall 50% increase in network lifetime. THC-RPL has 10% less message exchange and 0% storage costs.

Suggested Citation

  • Danyal Arshad & Muhammad Asim & Noshina Tariq & Thar Baker & Hissam Tawfik & Dhiya Al-Jumeily OBE, 2022. "THC-RPL: A lightweight Trust-enabled routing in RPL-based IoT networks against Sybil attack," PLOS ONE, Public Library of Science, vol. 17(7), pages 1-33, July.
    • Handle: RePEc:plo:pone00:0271277
    DOI: 10.1371/journal.pone.0271277
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    References listed on IDEAS

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    1. Chetan M. Bulla & Mahantesh N. Birje, 2021. "A Multi-Agent-Based Data Collection and Aggregation Model for Fog-Enabled Cloud Monitoring," International Journal of Cloud Applications and Computing (IJCAC), IGI Global, vol. 11(1), pages 73-92, January.
    2. Vipindev Adat & B. B. Gupta, 2018. "Security in Internet of Things: issues, challenges, taxonomy, and architecture," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(3), pages 423-441, March.
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