MedicalFuzzySec: A Novel Steganography Technique Using Fuzzy Logic to Secure EPD in Medical Images

Abstract

Medical diagnostic systems generate sensitive patient information that requires optimal protection during transmission and storage. Image steganography provides a secure method for embedding secret data, making it imperceptible to the naked eye. However, applying general image steganography directly to medical images can compromise the quality of the transmitted data, and the distortions make the image hosting the secret information appear suspicious and inaccurate for medical interpretation. This study introduces MedicalFuzzySec, a dedicated steganographic framework for concealing Electronic Patient Data (EPD) in medical images through fuzzy logic-guided difference expansion. The originality of MedicalFuzzySec lies in its adaptive embedding mechanism, which selectively identifies optimal pixel regions using fuzzy inference rules to ensure high data security with minimal impact on diagnostic image quality.

Authors

Moh Rosy Haqqy Aminy, Ntivuguruzwa Jean De La Croix, Tohari Ahmad, Emmanuel Bugingo, François Xavier Rugema

Publication Details

• Journal: Cyber Security and Applications
• Volume: 3
• Article: 100113
• Year: 2025
• Publisher: Elsevier / ScienceDirect
• ISSN: 2772-9184

Keywords

Steganography, Fuzzy Logic, Medical Images, Electronic Patient Data (EPD), Data Hiding, Difference Expansion

Key Results

• PSNR values ranging from 56.06 dB to 76.29 dB
• SSIM values from 0.989 to 0.999
• Adaptive embedding mechanism using fuzzy inference rules
• High imperceptibility and robustness for clinical image standards

View on ScienceDirect →