A Proof of Resource Blockchain‐Based Constitutive Recurrent Neural Network Model for Quality‐Centric Resource Management in Wireless Sensor Networks

ABSTRACT Wireless sensor networks (WSNs) have gained significant attention in recent years owing to their important role in enhancing various daily life services, including military operations, healthcare, and social applications. Routing protocols often face challenges posed by malicious nodes that disrupt network performance. Therefore, a proof of resource blockchain‐based constitutive recurrent neural network model for quality‐centric resource management in wireless sensor networks (PRB‐CRNN‐QRWSN) is proposed in this paper. Here, the input data are collected from the WSN‐DS dataset, ensuring a robust data foundation for analysis. The collected data are provided to an innovative framework that leverages a constitutive recurrent neural network (CRNN) to effectively detect malicious nodes in the network. Then the proof of resource (PoR) is used to securely register legitimate nodes. The proposed PRB‐CRNN‐QRWSN achieves better performance of 22.13%, 24.14%, and 21.07% lower delay and 22.13%, 24.14%, and 21.07% higher throughput when compared to the existing methods: blockchain‐depend deep‐learning‐driven architecture for quality routing in WSN (BDL‐AQR‐WSN), blockchain‐depend secure localization against malicious nodes in IoT‐depend WSN utilizing federated learning (BSL‐WSN‐FL), and detection of denial‐of‐service attack in WSN: a lightweight machine learning approach (DDSA‐WSN‐LMLA), respectively.