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Dual attention-based deep learning with blockchain for multimedia data processing and secure access control in IoHT

G. K. Reddy,Nageswara Rao Lavuri,Shabana Urooj,Krishna Dharavath,Nidal Nasser,Y. J

Published 2025 in Scientific Reports

ABSTRACT

The Internet of Medical Things represents an interconnected medical technology that comprises mobile applications, medical services, as well as networks. These medical equipment and software are connected to medical systems across an internet connection. Security and confidentiality of healthcare information, flexibility, and data availability are the most complicated IoT problems to tackle. The utilization of multimedia in medical systems permits the collection, processing, and delivery of clinical data in many different types of styles, comprising texts, images, and speech, throughout the web via different effective components. Yet, processing huge quantities of information, such as every individual’s findings and images, demands additional human labour and represents safety risks. The fundamental architecture characteristics of blockchain systems including robust data encryption and strong peer-to-peer systems are beneficial and affordable options for addressing a few of these demands. Similarly, Blockchain-aided devices are effective in the field of medical science, due to their resource distribution and verification processes that enable access to information. Current investigations struggle to understand the rising need for enhanced data integration over distinct clinical services and platforms, which results in the evolution of application-centric approaches to patient-centric applications. Therefore, this work presented the efficient multimedia data processing in Internet of Healthcare Things (IoHT) based on Blockchain technology. For the improvement of healthcare resource distribution and to avoid the risk in IoHT, efficient blockchain technology is initiated to manage the security control in a real-time system. Further, the access control is managed by developing the advanced model called Dual Attention-based Deep Bayesian Network (DA-DBN). The developed system provides the secured framework for the multimedia content in IoHT using blockchain technology and DA-DBN by generating a hash of each data. This process helps in determining the changes or alterations in the blockchain. Finally, the performance of the proposed scheme concerning the blockchain is validated against the conventional approach. The result demonstrates the potential of the proposed system in securing the IoHT-based health management. The outcomes reveal that the proposed DA-DBN achieved 23.88% faster access control than SVM leading to improved efficiency and enhanced security. Therefore, the proposed model is well suited for multimedia data processing and secure access to the IoHT applications.

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