Decentralised access control framework for IoT security by leveraging blockchain technology in smart farming

Integrating the Internet of Things (IoT) in smart farming has led to significant advancements in agricultural ecosystems. Smart farming aims to enhance performance and production quality by automating various processes. However, the rapid adoption of IoT in smart farming has introduced cybersecurity threats, particularly related to access control. Existing access control models in IoT, Discretionary Access Control (DAC), Mandatory Access Control (MAC), Role-Based Access Control (RBAC), Attributed-Based Access Control (ABAC) Organisation-Based Access Control (OrBAC), Usage-Based Access Control (UCON), Capability-Based Access Control (CapBAC), and Hybrid-Based Access Control (HBAC), are common centralized and face challenges in scalability and efficiency within IoT ecosystems. Thus, in this study proposed framework adapting blockchain technology to create a secure and decentralised approach for securing and protecting IoT devices from unauthorised access by anomalous entities. The framework is built upon a four-layer architecture by adapting the FRABAC model, a combination of RBAC and ABAC to develop finegrained access control policies that are enforced through smart contracts on the blockchain. The research demonstrates the effectiveness and validation of the decentralised access control mechanism through simulation experiments and blockchain performance metrics evaluation. The evaluation results highlight that the proposed framework demonstrates low-cost consumption when paying transaction fees for executing the smart contracts of IoT_SRMC, IoT_ORMC, and IoT_ACC. Additionally, the evaluation reveals that the addDevice() and addResource() operations experienced slightly higher latencies of 363161ms and 367382ms, respectively, in the case of 150 requested transactions. In contrast, the addTypeRLItem() operation demonstrated a lower latency of 905ms in 150 transaction requests compared to the addDevice() and addResource() operations. While the transaction throughput of addDevice(), addTypeRLItem() operations has reveal high transaction throughput of 75 tps at 150 requested transaction, and addResource() operations has reveal slightly low transaction throughput of 37.5 tps at 150. Thus, the findings in this study have the potential to address scalability, heterogeneity, low-cost consumption, and resource constraints related to IoT devices and applicable to apply in smart farming practices. Additionally, it serves as a foundation for formatting access policies in multiple entities and heterogeneous IoT environments across any IoT domain, requiring specific justifications for identification. The study establishes a basis for future advances in ensuring secure access to IoT devices and resources across diverse domains and opens new opportunities for researchers to apply decentralised access control for the IoT environment.