Open Access

ARTICLE

Collaborative Detection and Prevention of Sybil Attacks against RPL-Based Internet of Things

Muhammad Ali Khan¹, Rao Naveed Bin Rais^2,*, Osman Khalid¹

1 Department of Computer Science, COMSATS University Islamabad, Abbottabad Campus, Abbottabad, Pakistan
2 Artificial Intelligence Research Center (AIRC), Ajman University, Ajman, United Arab Emirates

* Corresponding Author: Rao Naveed Bin Rais. Email:

Computers, Materials & Continua 2023, 77(1), 827-843. https://doi.org/10.32604/cmc.2023.040756

Received 29 March 2023; Accepted 01 August 2023; Issue published 31 October 2023

Abstract

The Internet of Things (IoT) comprises numerous resource-constrained devices that generate large volumes of data. The inherent vulnerabilities in IoT infrastructure, such as easily spoofed IP and MAC addresses, pose significant security challenges. Traditional routing protocols designed for wired or wireless networks may not be suitable for IoT networks due to their limitations. Therefore, the Routing Protocol for Low-Power and Lossy Networks (RPL) is widely used in IoT systems. However, the built-in security mechanism of RPL is inadequate in defending against sophisticated routing attacks, including Sybil attacks. To address these issues, this paper proposes a centralized and collaborative approach for securing RPL-based IoT against Sybil attacks. The proposed approach consists of detection and prevention algorithms based on the Random Password Generation and comparison methodology (RPG). The detection algorithm verifies the passwords of communicating nodes before comparing their keys and constant IDs, while the prevention algorithm utilizes a delivery delay ratio to restrict the participation of sensor nodes in communication. Through simulations, it is demonstrated that the proposed approach achieves better results compared to distributed defense mechanisms in terms of throughput, average delivery delay and detection rate. Moreover, the proposed countermeasure effectively mitigates brute-force and side-channel attacks in addition to Sybil attacks. The findings suggest that implementing the RPG-based detection and prevention algorithms can provide robust security for RPL-based IoT networks.

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Keywords

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