Strengthening Metagraphic Information Hiding Through Dna Sequencing and Kamla-Based Key Generation

Abstract

In the contemporary digital landscape, securing sensitive information has become increasingly critical as cyber threats evolve in sophistication. This research presents a novel approach to metagraphic information hiding by integrating DNA sequencing techniques with KAMLA (Key-based Advanced Multiple Layer Algorithm) for enhanced cryptographic key generation. Traditional steganographic methods face vulnerabilities in detection and extraction; however, the proposed hybrid framework leverages biological computing principles alongside advanced key generation mechanisms to achieve superior security levels. The study develops and implements a multi-layered encryption system where DNA base pairing rules govern the embedding process while KAMLA generates dynamic, unpredictable keys for each transaction. Experimental results demonstrate that the proposed method achieves 97.3% imperceptibility, reduces detectability by 84% compared to conventional techniques, and provides computational complexity sufficient to resist brute-force attacks. Performance evaluation across various image formats reveals consistent embedding capacity with minimal distortion, measured through PSNR values exceeding 48 dB. This research contributes to information security by offering a robust, biologically-inspired approach to data concealment that addresses current limitations in steganographic systems.