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

Danyal Arshad1, Muhammad Asim1, Noshina Tariq2

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This study introduces a Trust-based Hybrid Cooperative RPL protocol (THC-RPL) to combat internal attacks in the Internet of Things (IoT). THC-RPL effectively detects malicious nodes, enhancing network security and extending device lifespan.

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Area of Science:

  • Computer Science
  • Network Security
  • Internet of Things (IoT)

Background:

  • The Internet of Things (IoT) integrates technologies like Mobile Ad hoc Networks (MANETs) and Wireless Sensor Networks (WSNs).
  • The Routing Protocol for Low power and Lossy networks (RPL) is crucial for IoT but vulnerable to internal attacks.
  • Existing security measures like Intrusion Detection Systems (IDS) have high computational overhead for IoT devices.

Purpose of the Study:

  • To propose a novel Trust-based Hybrid Cooperative RPL protocol (THC-RPL) for enhanced security in RPL-based IoT networks.
  • To specifically address the detection of malicious Sybil nodes within the IoT infrastructure.
  • To evaluate the performance of THC-RPL against existing state-of-the-art methods.

Main Methods:

  • Development of a Trust-based Hybrid Cooperative RPL protocol (THC-RPL).
  • Implementation of cooperative mechanisms for enhanced threat detection.
  • Comparative analysis and performance evaluation against current security protocols in IoT networks.

Main Results:

  • THC-RPL demonstrates superior performance in detecting attacks compared to existing methods.
  • Maintains a packet loss ratio between 15-25% and average energy consumption of 60-80 mJ.
  • Achieves approximately 40% greater energy conservation and a 50% increase in network lifetime.

Conclusions:

  • THC-RPL effectively mitigates internal attacks, particularly Sybil nodes, in IoT networks.
  • The protocol offers significant improvements in energy efficiency and network longevity.
  • THC-RPL presents a viable, low-overhead security solution for resource-constrained IoT environments.