A Novel 3D Reversible Data Hiding Scheme Based on Integer-Reversible Krawtchouk Transform for IoMT.

Area of Science:

• Digital Image Processing
• Data Security and Privacy
• Medical Imaging

Background:

• Floating-point Krawtchouk transform in image processing suffers from rounding errors due to limited significant digits.
• Existing 2D reversible data hiding (RDH) algorithms have limitations for large-scale medical image data.
• The Internet of Medical Things (IoMT) requires secure methods for storing and transmitting extensive medical data.

Purpose of the Study:

• To introduce an integer and reversible Krawtchouk transform (IRKT) to overcome rounding errors in image processing.
• To propose a novel 3D RDH algorithm based on IRKT for secure medical data embedding in IoMT.
• To enhance the security and efficiency of medical data storage and transmission in the IoMT sector.

Main Methods:

• Developed an integer and reversible Krawtchouk transform (IRKT) generating integer coefficients.
• Designed a 3D RDH algorithm utilizing the IRKT for embedding data into 3D medical images.
• Conducted extensive experimental evaluations to assess embedding capacity, imperceptibility, and security.

Main Results:

• The proposed IRKT generates integer coefficients, suitable for lossless image applications.
• The IRKT-based 3D RDH algorithm achieves high embedding capacity without increasing original image size.
• The algorithm demonstrates imperceptibility and resilience against statistical attacks, outperforming conventional 2D RDH methods.

Conclusions:

• The IRKT effectively addresses rounding errors in Krawtchouk transform applications.
• The novel 3D RDH algorithm provides a secure and efficient solution for medical data in IoMT.
• This approach enhances data security and integrity for massive medical data storage and transmission.