A New Genetic Algorithm Approach for Secure JPEG Steganography

Steganography is the act of hiding a message inside another message in such a way that can only be detected by its intended recipient. Naturally, there are security agents who would like to fight these data hiding systems by steganalysis, i.e. discovering covered messages and rendering them useless. There is currently no steganography system which can resist all steganalysis attacks. In this paper we propose a novel GA evolutionary process to make a secure steganographic encoding on JPEG images. Our steganography step is based on OutGuess which is proved to be the least vulnerable steganographic system. A combination of OutGuess steganalysis approach and maximum absolute difference (MAD) for the image quality are used as the GA fitness function. The model presented here is based on JPEG images; however, the idea can potentially be used in other multimedia steganography as well