ABSTRACT
This chapter presents a method for breaking steganalytic systems that is based on genetic algorithm (GA). It also presents GA-based breaking algorithms on spatial-domain steganalytic systems and frequency-domain steganalytic systems. The GA, introduced in a seminal work by J. H. Holland, is commonly used as an adaptive approach that provides a randomized, parallel, and global search based on the mechanics of natural selection and genetics in order to find solutions to a problem. An objective, called fitness function, is used to evaluate the quality of each chromosome. The chromosomes of high quality will survive and form a new population of the next generation. The chromosome is used to adjust the pixel values of a cover image to generate a stego-image, so the embedded message can be correctly extracted and at the same time the statistical features left intact in order to break steganalytic systems. A fitness function is used to evaluate the embedded message and statistic features.
