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<p>The Routing Protocol for Low Power and Lossy Networks (RPL), widely used in IoT networks, is increasingly vulnerable to routing attacks as IoT applications expand globally. The lack of built-in attack detection and mitigation mechanisms in RPL necessitates security enhancements, yet securing these networks is challenging due to limited computational resources, energy constraints, and the need to balance security with performance efficiency. To address these issues, we propose BLET-IoT, a Behavioral Link-Level and Energy-Aware Trust-based secure routing approach for RPL-based IoT networks. BLET-IoT evaluates the trustworthiness of nodes by combining node-level and link-level trust metrics, ensuring secure and adaptive routing. While BLET-IoT incurs a slight increase in energy consumption due to continuous trust monitoring, this trade-off yields a significantly higher packet delivery ratio (PDR) and improved attack detection, thereby outweighing the additional computational overhead. Simulation results using Contiki-NG Cooja show that BLET-IoT improves PDR by 30.64% over MRHOF and 17.91% over SecTrust-RPL while achieving 1.71% higher attack detection than SecTrust-RPL within the first 10&#xa0;min of operation in the static scenario. Moreover, experiments under dynamic conditions confirm that BLET-IoT continues to outperform SecTrust-RPL in terms of security and overall performance, demonstrating its effectiveness even when nodes are mobile. These findings underscore BLET-IoT’s robust and adaptive routing capabilities, making it a practical solution for securing IoT deployments in both static and dynamic environments.</p>

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Secure routing in RPL-based IoT networks considering behavioral trust and energy requirements

  • 期刊论文

  • 发表日期：

    2025年5月26日

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  • Fatemeh Vafaei Nejad,
  • Mohammad Mehdi Gilanian Sadeghi,
  • Mohammad Hossein Rezvani

摘要

The Routing Protocol for Low Power and Lossy Networks (RPL), widely used in IoT networks, is increasingly vulnerable to routing attacks as IoT applications expand globally. The lack of built-in attack detection and mitigation mechanisms in RPL necessitates security enhancements, yet securing these networks is challenging due to limited computational resources, energy constraints, and the need to balance security with performance efficiency. To address these issues, we propose BLET-IoT, a Behavioral Link-Level and Energy-Aware Trust-based secure routing approach for RPL-based IoT networks. BLET-IoT evaluates the trustworthiness of nodes by combining node-level and link-level trust metrics, ensuring secure and adaptive routing. While BLET-IoT incurs a slight increase in energy consumption due to continuous trust monitoring, this trade-off yields a significantly higher packet delivery ratio (PDR) and improved attack detection, thereby outweighing the additional computational overhead. Simulation results using Contiki-NG Cooja show that BLET-IoT improves PDR by 30.64% over MRHOF and 17.91% over SecTrust-RPL while achieving 1.71% higher attack detection than SecTrust-RPL within the first 10 min of operation in the static scenario. Moreover, experiments under dynamic conditions confirm that BLET-IoT continues to outperform SecTrust-RPL in terms of security and overall performance, demonstrating its effectiveness even when nodes are mobile. These findings underscore BLET-IoT’s robust and adaptive routing capabilities, making it a practical solution for securing IoT deployments in both static and dynamic environments.