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    Area of Science:

    • Computer Science
    • Medical Informatics
    • Cybersecurity

    Background:

    • Cloud-based medical image storage raises privacy concerns.
    • Existing content-based image retrieval (CBIR) systems often require decryption, compromising security.
    • Secure retrieval from encrypted databases is crucial for healthcare.

    Purpose of the Study:

    • To propose a novel secure content-based image retrieval (SCBIR) system for cloud frameworks.
    • To enable physicians to retrieve similar medical images from encrypted databases without decryption.
    • To ensure end-to-end security in the image retrieval process.

    Main Methods:

    • Developed a SCBIR system utilizing homomorphic encryption.
    • Employed two non-colluding, honest-but-curious servers for secure feature processing.
    • Encrypted image features using homomorphic encryption before retrieval.
    • Tested the system on a diabetic retinopathy image database.

    Main Results:

    • The proposed SCBIR system successfully retrieves images from an encrypted database without decryption.
    • Experimental results demonstrate retrieval performance comparable to non-encrypted image processing.
    • The system ensures end-to-end security through encrypted features and homomorphic encryption.

    Conclusions:

    • The novel SCBIR system offers a secure and effective solution for retrieving medical images in cloud environments.
    • Homomorphic encryption and a two-server architecture provide robust data privacy.
    • The system maintains high retrieval accuracy, making it suitable for clinical applications.