ROUTING PROTOCOL FOR LOW-POWER AND LOSSY NETWORKS (RPL): SECURITY ATTACKS, DEFENSE STRATEGIES, AND RESEARCH TRENDS FOR IOT

Abstract

Routing Protocol for Low Power and Lossy Networks (RPL) is the routing The rapid expansion of the Internet of Things (IoT) has led to the deployment of billions of interconnected low-power devices across smart homes, healthcare, industrial automation, environmental monitoring, and smart city applications. The Routing Protocol for Low-Power and Lossy Networks (RPL) has emerged as the standard IPv6 routing protocol for resource-constrained IoT networks because of its lightweight design, scalability, and energy-efficient routing capabilities. Despite these advantages, RPL incorporates only basic security mechanisms, making it vulnerable to a wide range of routing attacks that threaten the confidentiality, integrity, availability, authenticity, and reliability of IoT communications. Attacks such as sinkhole, blackhole, wormhole, selective forwarding, Sybil, rank, version number, DIS flooding, DODAG inconsistency, and replay attacks can significantly degrade network performance and compromise critical IoT services.

This review presents a comprehensive analysis of RPL security by systematically examining existing attack models, detection mechanisms, prevention strategies, and defense frameworks reported in recent literature. The reviewed studies are classified according to the Confidentiality, Integrity, and Availability (CIA) security model and further categorized based on attack objectives, network layer, attacker capabilities, and routing behavior. Existing countermeasures—including cryptographic approaches, trust-based routing, intrusion detection systems, blockchain-based security, machine learning, deep learning, and explainable artificial intelligence (XAI)-enabled detection techniques—are critically compared in terms of detection accuracy, computational overhead, energy efficiency, scalability, and implementation complexity. In addition, this review identifies benchmark simulation tools, datasets, evaluation metrics, and emerging research trends to provide a comprehensive understanding of the current state of RPL security.

Finally, the paper highlights key research challenges, including resource constraints, real-time intrusion detection, secure routing in heterogeneous IoT environments, privacy preservation, explainability of intelligent security models, and resilience against sophisticated routing attacks. Future research opportunities involving Federated Learning, Graph Neural Networks (GNNs), Large Language Models (LLMs), blockchain, Edge AI, Zero Trust architectures, and lightweight post-quantum cryptography are also discussed. This review provides researchers and practitioners with a structured reference for designing secure, scalable, and intelligent RPL-based routing solutions for next-generation IoT systems.