Genetic Algorithm to Make Persistent Security and Quality of Image in Steganography from RS Analysis

TL;DR

This paper introduces a genetic algorithm-based steganography technique that enhances the security and quality of color images against RS steganalysis by optimizing the embedding process through natural evolution.

Contribution

It proposes a novel genetic algorithm approach to improve the robustness of steganography against RS analysis in color images, which is not addressed by existing methods.

Findings

Enhanced security against RS steganalysis in color images

Optimized image quality through genetic algorithm

Effective preservation of secrecy during communication

Abstract

Retention of secrecy is one of the significant features during communication activity. Steganography is one of the popular methods to achieve secret communication between sender and receiver by hiding message in any form of cover media such as an audio, video, text, images etc. Least significant bit encoding is the simplest encoding method used by many steganography programs to hide secret message in 24bit, 8bit colour images and grayscale images. Steganalysis is a method of detecting secret message hidden in a cover media using steganography. RS steganalysis is one of the most reliable steganalysis which performs statistical analysis of the pixels to successfully detect the hidden message in an image. However, existing steganography method protects the information against RS steganalysis in grey scale images. This paper presents a steganography method using genetic algorithm to protect against the RS attack in colour images. Stego image is divided into number of blocks. Subsequently, with the implementation of natural evolution on the stego image using genetic algorithm enables to achieve optimized security and image quality.