Background The growing digitization of healthcare systems requires robust procedures to protect patient privacy and guarantee the integrity of medical imaging data during storage and transmission. This paper presents a comprehensive security architecture combining cryptography, sensitive data compression, and steganography as the third essential component for medical image protection. Methods The proposed framework employs unique steganographic techniques using Least Significant Bit (LSB) substitution during embedding and extraction stages. The Modified Kekre Algorithm (MKA), optimized for medical imaging environments, enhances data hiding capacity. A variable-length approach based on Modified Run Length Encoding (MRLE) doubles secret information payload within CoverImages compared to conventional methods. Results Experimental validation demonstrates that generated StegoImages remain nearly indistinguishable from original medical photographs under statistical analysis and visual inspection. The technique exhibits strong resistance against single value domain detection attacks, particularly the RS (Regular-Singular) steganalysis assault. Conclusions The proposed steganographic framework guarantees security and reliability of secret medical data in clinical settings, maximizing storage efficiency without compromising image quality while providing robust defense against advanced steganalysis detection methods.
Khalaf et al. (Mon,) studied this question.