关键词: 最不重要位匹配, 隐写检测, 二阶差分, Markov特征

Abstract: In this paper, the author put forward a Least Significant Bit (LSB) matching steganalytic algorithm. Through calculating the second-order differential of the image pixels on horizontal and vertical directions, the differential matrix was obtained and it was used as sensitive feature extracting source and the second-order Markov transformation matrix of the differential matrix was extracted as the features, according to the LSB matching steganography with high security. According to the experimental result shows that the algorithm proposed in the paper speedups the detection process in a large extent and enhances the performance and practicability of the steganalytic algorithm while maintaining high detection accuracy, compared with the algorithms based on first-order differential Markov transition probability matrix.

Key words: Least Significant Bit (LSB) matching, steganalysis, second-order differential, Markov feature