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The Internet of Medical Things (IoMT) is a rapidly growing field involving the use of interconnected medical devices, sensors and systems for healthcare applications. The use of IoMT has the potential to revolutionize the healthcare industry by improving patient medication outcomes, increasing efficiency and reducing costs. However, the widespread adoption of IoMT also raises concerns about privacy and security, as it involves collecting, processing and sharing sensitive medical data. One of the main challenges in IoMT lies in ensuring the privacy and security of medical data while enabling the necessary data sharing and analysis to support healthcare applications. To address the limitations and ongoing challenges in this field, this paper presents a state-of-the-art system that utilizes permissioned blockchain and fully homomorphic encryption optimization to preserve medical data privacy in IoMT systems. The application of hybrid data classification before encryption is proposed, as this would enhance privacy and reduce processing time. For the Saudi healthcare sector, this hybrid classification model will involve a combination of the Health Insurance Portability and Accountability Act (HIPPA) identifiers and the Saudi Authority for Data and Artificial Intelligence (SDAIA) personal data protection standards. The latest technologies will be utilized in this research to achieve the highest level of performance and enhance data privacy.
Alsadhan et al. (Tue,) studied this question.