基于拉普拉斯算子统计量的LSB替换隐写分析方法
doi: 10.3724/SP.J.1146.2008.00596
Detection Methods for LSB Embedding Based on Laplacian Statistics
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摘要: 该文基于对图像像素点的拉普拉斯算子统计量的分析,提出了两种新的LSB替换隐写分析方法。首先定义了描述像素点与4-邻域像素均值关系的统计量,进而通过对隐秘信息的嵌入、LSB平面二次嵌入和LSB平面置反带来的变化分析,提出了隐秘信息的检测方法1和隐写嵌入率的准确估计方法2。该文提出的二个方法实际物理意义明显,实现简单。实验结果表明在嵌入率不小于20%时方法2估计准确率优于RS方法。Abstract: Two new steganalysis methods for the Least Significant Bit (LSB) embedding technique are proposed based on the analysis of the laplacian statistics of image pixel. The relation between the current pixel and its four-neighborhood pixel average is defined as statistics, then we propose the method 1, which can detect the existence of hidden messages, and the method 2, which can accurately estimate the amount of hidden messages. These two methods are based on the analysis of effects brought by message embedding, embedding twice and LSB plane flipping. These two methods have remarkable physical significances and can be implemented conveniently. Experimental results show that the estimating precision of method 2 is better than that of the RS method if the embedding ratio is not less than 20%.
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