Pixel Group Trace Model-Based Quantitative Steganalysis for Multiple Least-Significant Bits Steganography
Chunfang Yang, Fenlin Liu, Xiangyang Luo, Ying Zeng · IEEE Transactions on Information Forensics and Security · 2012
For analyzing the multiple least-significant bits (MLSB) steganography, a pixel group trace model is presented. Based on this model and some statistical characteristics of images, two quantitative steganalysis methods are proposed for two typical MLSB steganography paradigms. The pixel group trace model simulates the MLSB embedding by exclusive or operation, and traces the transition relationship among the possible structures of the pixel group's value by some trace pixel group subsets. Then, the estimation equations of embedding ratio are derived from the transition probability matrix among trace subsets and the symmetry of regular and singular pixel group sets. Finally, a series of experimental results for the case of triple pixel group show that the proposed steganalysis methods can estimate the low embedding ratio with smaller error, especially, for some cases, the interquartile range of the estimation errors is smaller than the best one of the others by more than 45%.