Improved diagonal queue medical image steganography using Chaos theory, LFSR, and Rabin cryptosystem

Area of Science:

• Medical Imaging
• Cryptography
• Information Security

Background:

• Secure transmission of sensitive patient medical data is critical.
• Existing steganography techniques may have limitations in security and embedding capacity.
• Previous work by Jain and Lenka (2016) provides a foundation for improvement.

Purpose of the Study:

• To propose an improved diagonal queue medical image steganography algorithm.
• To enhance the security and efficiency of patient secret medical data transmission.
• To improve upon the technique described by Jain and Lenka (2016).

Main Methods:

• Generation of pseudo-random sequences using a linear feedback shift register and a standard chaotic map.
• Permutation and XORing of data using the generated pseudo-random sequences.
• Encryption of data using the Rabin cryptosystem.
• Steganography implementation using improved diagonal queues for embedding data into medical images.

Main Results:

• Security analysis was performed to evaluate the algorithm's robustness.
• Performance was assessed using Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR).
• Maximum embedding capacity and histogram analysis were conducted on brain disease stego and cover images.

Conclusions:

• The proposed improved diagonal queue steganography offers enhanced security for medical data transmission.
• The technique demonstrates effective data hiding capabilities with measurable performance metrics.
• Further analysis confirms the viability of the method for brain disease image steganography.