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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Journal of Electronics, Electromedical Engineering, and Medical Informatics
Croix, Ntivuguruzwa Jean De La
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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MedProtect: Protecting Electronic Patient Data Using Interpolation-Based Medical Image Steganography Muhammad, Aditya Rizki; Ramadhan, Irsyad Fikriansyah; Croix, Ntivuguruzwa Jean De La; Ahmad, Tohari; Uwizeye, Dieudonne; Kantarama, Evelyne
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 7 No 4 (2025): October
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v7i4.977

Abstract

Electronic Patient Records (EPRS) represent critical elements of digital healthcare systems, as they contain confidential and sensitive medical information essential for patient care and clinical decision-making. Due to their sensitive nature, EPRs frequently face threats from unauthorized intrusions, security breaches and malicious attacks. Safeguarding such information has emerged as an urgent concern in medical data security. Steganography offers a compelling solution by hiding confidential data within conventional carrier objects like medical imagery. Unlike traditional cryptographic methods that merely alter the data representation, steganography conceals the existence of the information itself, thereby providing discretion, security, and resilience against unauthorized disclosure. However, embedding patient information inside medical images introduces a new challenge. The method must maintain the image's visual fidelity to prevent compromising diagnostic precision, while ensuring reversibility for complete restoration of both original imagery and concealed information. To address these challenges, this research proposes MedProtect, a reversible steganographic framework customized for medical applications. MedProtect procedure integrates pixel interpolation techniques and center-folding-based data transformation to insert sensitive records into medical imagery. This method combination ensures accurate data recovery of the original image while maintaining the image quality of the resulting image. To clarify the performance of MedProtect, this study evaluates two well-established image quality metrics, Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM). The discovery shows that the framework achieves PSNR values of 48.190 to 53.808 dB and SSIM scores between 0.9956 and 0.9980. These outcomes display the high level of visual fidelity and imperceptibility achieved by the proposed method, underscoring its effectiveness as a secure approach for protecting electronic patient records within medical imaging systems.
A hybrid steganography scheme with reduced difference expansion and pixel-value ordering Putra, I Kadek Agus Ariesta; Croix, Ntivuguruzwa Jean De La; Ahmad, Tohari
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i5.pp3563-3575

Abstract

Steganography embeds secret messages into public media while ensuring the stego content remains visually indistinguishable from the original. The primary challenge lies in maximizing embedding capacity and image quality without introducing noticeable distortions. This research proposes a novel reversible data hiding (RDH) scheme that integrates reduced difference expansion (RDE) with four directional pixel-value ordering (PVO) schemes, horizontal, vertical, diagonal-right, and diagonal-left, to enhance embedding efficiency and visual fidelity. Unlike existing RDH methods that apply RDE with fixed or limited PVO directions, the proposed scheme dynamically selects the optimal PVO orientation based on pixel pair characteristics, effectively improving local prediction accuracy and reducing embedding-induced distortion. Previous studies have largely overlooked this relationship between pixel pair selection and embedding performance. Experimental evaluation on medical images with secret data sizes ranging from 5 kb to 100 kb demonstrates significant gains over recent PVO-based methods. The proposed method increases the average embedding capacity from 0.8315 to 0.9781 bit per pixel (bpp) (a 17.6% improvement) and raises the average peak signal-to-noise ratio (PSNR) from 49.44 to 53.40 dB, reducing distortion by approximately 3.96 dB.
Co-Authors Kantarama, Evelyne Muhammad, Aditya Rizki Putra, I Kadek Agus Ariesta Ramadhan, Irsyad Fikriansyah Tohari Ahmad Uwizeye, Dieudonne