A New Approach for Block Based Steganalysis Using a Multi-classifier

The aim of the recent block-based steganalysis approaches, is to detect and differentiate cover and stego images. In this research, the discovering capability of the steganography algorithm was used for a sample stego image by designing a multi classifier. This kind of classification was used for the steganalysis of smaller blocks of an image. Because normal images mostly have heterogeneous regions, first, the main image was decomposed into smaller blocks which were similar. Then, these similar blocks were put in the same class. Therefore, several different classes were obtained, for each of which, an appropriate classifier was identified. This approach led to making a decision for identifying the situation of the image blocks that were either cover or stego and identifying the steganography algorithm used in stego images.