A novel blockchain-based clustering model for linked open data storage and retrieval

In recent years, organizations have increasingly adopted blockchain technology to facilitate the open sharing of data with other entities. However, despite its potential benefits, blockchain-based open data models face several challenges, including scalability, timely access, and privacy concerns. This paper introduces a Novel Blockchain-based Clustering Model for Linked Open Data Storage and Retrieval called BCLOD to address these challenges. Initially, network nodes are organized into clusters, and transactions from users within each cluster are then grouped into a proposed linked block specific to that cluster to preserve linked open data property. Additionally, we introduce a new partial block structure, which stores parts of the linked block. To enhance scalability and trustworthiness, we propose the structures of partial and full chains in BCLOD for storing the linked and the partial blocks. Furthermore, a two-layer Role-Based Access Control (RBAC) mechanism is introduced to safeguard user privacy. To validate the effectiveness of BCLOD, we conduct evaluations using various scenarios. The results demonstrate a significant reduction in the required storage space for both partial and full chains when compared to the traditional blockchains. Besides, BCLOD prevents fork occurrences and potential attacks such as Sybil, Distributed Denial of Service (DDoS), and Eclipse.