Design of an Efficient QOS Aware Trust-Based Security Model with Bioinspired Sidechains for Healthcare Deployments

Increased adoption of blockchain technology in healthcare systems has paved the way for transparent and secure data management. However, the inherent difficulties of scalability, performance, and security in blockchain networks necessitate the development of efficient models to ensure Quality of Service (QoS) and reliability. In this paper, we propose a novel QoS-aware trust-based security model for healthcare blockchain deployments that addresses these challenges by taking temporal energy consumption, temporal delay, temporal throughput, and temporal Packet Delivery Ratio (PDR) levels into account when selecting miner nodes. For efficient miner node selection, our model employs trust-based analysis. While for the formation of sidechains an efficient Grey Wolf Optimizer (GWO) Model is used, which is a metaheuristic technique inspired by hunting behaviour of Wolves in real-time scenarios. Effectively balancing the trade-off between exploration and exploitation, the GWO algorithm enables the selection of optimal miner nodes that meet the desired QoS requirements. By incorporating temporal metrics, our model adapts dynamically to changing network conditions, ensuring optimal resource utilization and enhanced network performance levels. To assess the efficacy of our proposed model, we ran extensive simulations and compared its performance to that of existing sidechaining models. The outcomes demonstrate significant enhancements in multiple aspects. In comparison to state-of-the-art sidechaining models, our model achieves an impressive 8.5% reduction in delay, 3.9% reduction in energy consumption, 4.5% increase in throughput, and 2.5% improvement in PDR levels. These enhancements demonstrate the efficacy and efficiency of our healthcare blockchain deployment models. The proposed model has applications in a variety of real-time healthcare scenarios. It can be used in electronic health record (EHR) systems where data integrity, confidentiality, and accessibility are crucial. By ensuring QoS-aware miner node selection, our model contributes to dependable and efficient data management, allowing for streamlined access to patient records while maintaining the necessary security standards. Moreover, the trust-based approach of our model improves the overall security of healthcare blockchain deployments. Our model reduces the risks associated with malicious or compromised miner nodes by incorporating trustworthiness metrics such as reputation and behavior analysis. This is especially important in the healthcare industry, where the sensitive nature of patient data necessitates stringent security measures.