Enhanced Steganography in the Frequency Domain: A Daubechies Wavelet Transform Approach with Genetic Algorithm Optimization (ADWTGA)

Abstract

In today's digital age, the authenticity and integrity of image are predominant in security, forensics and digital media. In this paper a novel steganographic technique in frequency domain employing Daubechies wavelet transform (DWT) and Genetic Algorithm has been proposed to enhance image authentication processes. By leveraging the multi-resolution capabilities of DWT, authenticating image bits are embedded within the transformed coefficients of the cover image while maintaining visual quality. The energy compaction property of the Daubechies wavelets is effectively utilized by this technique to embed data that is robust against common image processing attacks such as compression and noise addition. The proposed approach achieves high embedding capacity without compromising fidelity of the cover image by applying Genetic Algorithm. Furthermore, the experimental results demonstrate that this method provides reliable extraction mechanisms for verifying the authenticity of the image. The proposed Daubechies Wavelet based steganographic technique with Genetic Algorithm represents a significant advancement in secure image transmission and validation frameworks, paving the way for enhanced methods of digital content protection.