Real-time multi-level trust-based secure routing for improved QoS in WSN using blockchain
Srihari Ramachandra, M. Baskar · Results in Engineering · 2025
• Improving the QOS performance in Wireless Sensor Networks by adapting the blockchain with trust-based secure routing. • The Model considers various features of neighboring nodes in the network and analyzes their trust in selecting a secure route. The model collects different features of the wireless node from different transmissions and analyzes the trust in a local manner, as well as claims the trust of nodes from different neighboring nodes. • Trust-based secure routing by considering various features of the nodes in the network during the data transmission. • When blockchain technology is combined with the trust-based model, energy is lost due to various processing requirements. This is known as the energy overhead, which is less in the proposed method. With the scope to improve the QoS performance of WSNs, various approaches are discussed in the literature. Analyzing the trust of nodes in real-time is essential to enforce secure routing due to the heterogeneity of nodes. Also, the trust must be measured at various levels of the routing process to achieve higher performance in secure routing, because locally measuring the trust of nodes would not be effective due to the least availability of transmission data which encourages the need to measure the trust globally and helps to enforce rigid routing process. On the other side, adapting blockchain with trust-based routing would stimulate the data security and routing performance of WSNs. With all these concerns, an efficient Multi-Level Trust Based Secure Routing (MLTSR-BC) is presented. The proposed model considers various features of neighboring nodes in the network to analyze the trust toward the selection of a secure route. The model uses transmission rate, retransmission rate, energy, frequency, and success rate to measure the trust of any node. The model collects different features of the wireless node from different transmissions and analyzes the trust in a local manner as well as claims the trust of nodes from different neighboring nodes. The model estimates the Localized Trust Factor (LTF) and Globalized Trust Factor GTF towards the selection of a secure route. The source node is involved in measuring LTF whereas an intermediate node would measure GTF value. Further, the method adapts the Adaptive Blockchain Security Algorithm for secure transmission of data between the nodes of the network. By incorporating multi-level trust analysis and integrating blockchain, the proposed model enhances the QoS performance of WSNs.