ScholarWorks@숙명여자대학교

초록

Medical supply chains face critical challenges in balancing transparent data access with privacy protection while maintaining environmental sustainability. Organizations must share crucial information like production specifications and environmental monitoring data, yet protect sensitive information such as proprietary formulations and patient records. Traditional access control mechanisms use centralized approaches that lack transparency, create single points of failure, and cannot adapt to the complex data sharing requirements of Artificial Intelligence (AI)-based Internet of Things (IoT) (AIoT) -enhanced green medical supply chains. To address these challenges, we propose green blockchain hierarchical AIoT-enhanced medical supply chain (G-BHAIMS), a novel framework that enables secure, energy-efficient data access control. G-BHAIMS employs a multi-chain architecture that segregates sensitive medical data storage from access control operations, while integrating environmental monitoring through AIoT devices. Our framework introduces a hierarchical access control model with data classification based on sensitivity levels and ecological impact factors, implemented through energy-efficient smart contracts. Experimental results demonstrate that G-BHAIMS achieves a 98.5% correct access decision rate, outperforming the best baseline method by 2.5 percentage points. The framework maintains an average execution time of 22ms (21.4% faster than comparable systems) and throughput above 95 TPS under heavy loads. Most significantly, G-BHAIMS reduces energy consumption by 17.8% and decreases carbon emissions by 16.1% compared to the best alternative approach, aligning security requirements with green supply chain principles.

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