Image Steganalysis Based on Block Correlation and Markov Model in DCT Domain

A high-order statistical method is proposed to detect JPEG image steganography. In order to describe the correlations between image data and their spatial positions fully, both the intra-block and inter-block correlations among JPEG coefficients are utilized. The intra-block and inter-block difference arrays along horizontal, vertical, and zigzag directions are generated by using the difference between the absolute value of quantized block discrete cosine transform coefficients. Markov process is applied to modeling these difference arrays, and the second order statistics, which are transition probability matrices for all difference arrays, are adopted as feature vectors for steganalysis. The simulation results show that the proposed scheme has higher detecting rates than known schemes.