Hybrid, randomized and high capacity conservative mutations DNA-based steganography for large sized data.

Area of Science:

• Bioinformatics
• Cryptography
• Molecular Biology

Background:

• Traditional data hiding methods face limitations in capacity and security.
• Integrating biological concepts offers novel approaches for data security and storage.

Purpose of the Study:

• To propose a secure, high-capacity data hiding algorithm using cryptography and molecular biology.
• To enhance data security by integrating DNA Playfair cipher and exploiting DNA conservative mutations.

Main Methods:

• Data encryption using DNA Playfair cipher.
• Randomized steganography by exploiting DNA conservative mutations for data embedding.
• Utilizing codons to hide two bits per codon while preserving protein sequence properties.

Main Results:

• Achieved high data capacity by hiding two bits per codon with no payload.
• Demonstrated the lowest cracking probability to date through biological permutations.
• Validated algorithm scalability with large datasets (up to 3 megabytes) compared to existing methods.

Conclusions:

• The proposed algorithm offers a secure and high-capacity solution for data hiding.
• Exploiting DNA conservative mutations provides a robust method for data embedding.
• The algorithm shows significant advantages in capacity, security, and scalability over existing techniques.