An efficient steganography method based on reducing changes

In this paper, a new approach is presented which reduces the changes of embedding in the cover media. This paper introduces maximum tolerable changes as a property of images. At first, the secure capacity of a database is determined using an efficient method. Then, an appropriate cover image is selected based on the secure capacity and the similarity ratio of the secret message with the cover image. Then, by using an increasing similarity method based on Cellular Automata and Genetic Algorithm, the similarity rate of the secret message is increased with the embedding places of the cover. The proposed approach is a preprocessing step in steganography methods which can be used with all of the existing steganography methods on every type of cover media. The proposed approach can increase the security or with preservation same security, can increase the secure capacity. Experimental results show the effectiveness of the proposed approach in enhancing the security and increasing the secure capacity of stego images.