Blockchain‐Enabled Risk‐Aware RPL With Real‐Time Rank Evaluation and Trust‐Weighted Consensus for Secure IoT Routing

ABSTRACT The need for efficient routing arises in Internet of Things (IoT)–based networks that comprise low‐power and lossy nodes. Routing Protocol for Low‐Power and Lossy Networks (RPL) has multiple limitations, including rank manipulation attacks, inefficient energy utilization, poor link quality, and vulnerability to malicious nodes. Moreover, conventional routing metrics typically evaluate only a limited set of parameters and are unable to capture the multiple risks and dynamic behaviors encountered in practical IoT environments. To overcome these limitations, this research proposes a Blockchain‐enabled Risk‐Aware RPL (Bc‐RARPL) framework that enhances routing security, adaptability, and performance. The proposed framework establishes a unified routing architecture by integrating real‐time rank verification, Multi‐Attribute Utility Theory (MAUT)–based risk assessment, trust‐aware consensus, and blockchain‐based route validation into a continuous routing decision process. Each node evaluates candidate parent nodes using a composite risk utility score derived from multiple factors, including residual energy, link quality, latency, and node failure probability, thereby enabling secure and intelligent parent selection. Routing path optimization is performed using a risk‐aware decision‐making strategy supported by the Starfish Optimization Algorithm, which jointly minimizes energy consumption, improves route stability, and mitigates dynamic network risks. In addition, a lightweight Zigbee blockchain securely stores routing histories, node rankings, and risk values, whereas a Trust‐Weighted Byzantine Fault Tolerance (TW‐BFT) consensus protocol restricts validation to trusted nodes, thereby reducing the impact of malicious attacks. Experimental results demonstrate that the proposed framework achieves a packet delivery ratio of up to 96%, reduces end‐to‐end delay and energy consumption, and improves routing reliability while providing enhanced resilience against rank manipulation and insider attacks.