STEGANALYSIS OF DIGITAL IMAGES UNDER DIFFERENT CONTENT FULLNESS

Abstract

An improvement of the steganalytic method for detection of the presence of additional information in color digital images which showed high efficiency in identifying stegano formed by embedding of secret data only into one color component of the container is presented. The proposed method analyses digital image in the spatial domain and is based on the accounting of sequential color triads in the matrix of unique colors of the digital content. However, in the process of steganographic transformation cases of embedding of confidential data into two and three color components of images are possible that ensures the concealment of a larger amount of information and requires the improvement of the existing method of steganalysis. In the course of the conducted research the character of perturbations in the quantity of sequential triads of triplets in a matrix of unique colors as a result of embedding of additional information into two and three color components of images originally stored in a losses format was analyzed. Considering obtained results the parameters of the original method for detecting of stegano was refined. It has been established that the character of changes in the quantity of sequential triads of triplets as a result of steganographic transformation is different in cases of using containers in a losses format and containers in a lossless format. Based on the obtained data the steganalytic method has been improved by integrating it with the method of detection the fact of compression of digital content developed earlier. The developed method provides high efficiency in detecting stego formed with different degree of container fullness without reducing the accuracy of identifying the filled color components if the additional information was embedded into only one color component of the digital images. This method can be used as a basis for complex steganalysis of digital contents by using existing methods that analyzes color matrixes of images separately.