Steganographic system based on higher-order statistics

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Abstract
Universal blind steganalysis attempts to detect steganographic data without knowledge about the applied steganographic system. Farid proposed such a detection algorithm based on higher-order statistics for separating original images from stego images. His method shows an astonishing performance on current steganographic schemes. Starting from the statistical approach in Farid's algorithm, we investigate the well known steganographic tool Jsteg as well as a newer approach proposed by Eggers et al., which relies on histogram-preserving data mapping. Both schemes show weaknesses leading to a certain detectability. Further analysis shows which statistic characteristics make both schemes vulnerable. Based on these results, the histogram preserving approach is enhanced such that it achieves perfect security with respect to Farid's algorithm.

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