Research On Blind Detection Resistant Steganographic Algorithm For Images

Steganography is a technique of covert communication which securely transmits the secret messages hidden into an innocuous cover media using the data redundancy. Steganalysis, as the countermeasure of steganography, aims at attacking the steganography by detecting the presence of the secret messages.With the improvement of the steganography security, it is harder to carry out steganalysis of specific embedding methods by scanning features. As a result, the universal blind steganalysis which detects the presence of the messages based on the statistical differences between the cover and stego, has become an attractive hotspot in the domain of steganalysis.With the development of steganalysis , The performance and the applicability of the universal blind steganalysis become better and better. So, the capability of resisting the usual universal blind steganalysis is the most important aspect to evaluate the performance of the steganographic algorithm.In this paper, the statistical modeling of images is firstly discussed, and the strategy to resist the usual universal blind steganalysis and its security are analyzed, based on which, three universal blind steganalysis resistant steganographic algorithms are proposed. The main work and contributions of this thesis can be summarized as follows:1. A blind detection resistant steganographic algorithm for images based on the integer wavelet is proposed. The subband coefficients above the wavelet denoising threshold are chosen for data embedding and the histogram adjustment process is introduced at the location of the coefficients threshold to preserve the wavelet coefficients histogram. As most of the blind steganalysis algorithms detect the stego images based on the differences of the statistical distributions between cover and stego images, the proposed method can resist the blind detection techniques. Experimental results show that our method outperforms the previous steganographic methods such as LSB matching and Pixel-Value Differencing on the capability of resisting current typical universal blind steganalysis methods.2. Based on the analysis of the principles of the blind detection techniques, a steganographic algorithm which hides data by modifying the high frequency coefficients of the morphological wavelet is proposed. There are four subbands of an image after integer wavelet decomposing, which induces the superposition of wavelet coefficients when the image is reconstructed after embedding. Consequently the quincunx sampling lifting scheme is introduced to decompose images which avoids such problem for there are only two subbands after decomposing. The high frequency coefficients table is built to amend the embedding rules; meanwhile the histogram adjustment strategy is introduced when dealing with the coefficients threshold to preserve the histogram of wavelet coefficients.3. According to the analysis of the effect of the texture complexity on steganalysis, we propose a data hiding algorithm based on texture complexity and difference pixel value. Firstly, the image is decomposed into blocks, after which the texture complexity of each block is calculated and blocks with high complexity are selected. Then the difference pixel values on two directions of the selected blocks are computed to choose the edge areas. The secret messages are only embedded in the pixel-value differencing above the threshold. Experimental results verify its great capacity of resisting the universal blind steganalysis methods.Finally, the work of this thesis is summarized and the further research topics and directions of image steganography are discussed.