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    Area of Science:

    • Computer Science
    • Cybersecurity
    • Health Informatics

    Background:

    • Internet of Medical Things (IoMT) systems utilize blockchain for data storage, but face challenges in data searching, privacy, and security.
    • Existing IoMT blockchain solutions require enhanced security and efficient data retrieval mechanisms to ensure patient data integrity and trustworthiness.

    Purpose of the Study:

    • To propose a novel Binary Spring Search (BSS) technique integrated with a hybrid deep neural network for secure and trustworthy IoMT data management.
    • To enhance the security, privacy, and searchability of medical data stored on blockchain within IoMT environments.
    • To develop a patient-centered data access model ensuring secure, efficient, and decentralized management of Patient Health Records (PHR).

    Main Methods:

    • Developed a Binary Spring Search (BSS) technique based on group theory, combined with a hybrid deep neural network.
    • Integrated blockchain for immutable and decentralized data management, AI for data analysis and threat detection, and searchable encryption for secure queries.
    • Implemented secure key revocation and dynamic policy updates within the proposed framework.
    • Utilized Hyperledger Fabric (OrigionLab) for blockchain simulations.

    Main Results:

    • The proposed framework significantly reduces transaction times while maintaining high security levels for IoMT data.
    • Demonstrated enhanced data searchability and trustworthiness compared to existing methods.
    • The blockchain-based architecture ensures integrity and tamper-proof storage of medical data.

    Conclusions:

    • The novel BSS technique integrated with AI and blockchain offers a secure, efficient, and searchable solution for managing Patient Health Records (PHR).
    • The patient-centered model enhances data security and demonstrates a positive return on investment for healthcare systems.
    • The proposed framework addresses critical privacy and security concerns in IoMT data searching and storage.