Improved LSB-matching Steganography for Preserving Second-order Statistics

In the paper, for enhancing the security of the traditional LSB matching, two improved LSB-matching methods are proposed. In the steganograhical procedure, the Markov chain distance based on the second-order statistics is chosen as the security metric to control the modification directions of ±1 embedding. The first method is based on stochastic modification, which directly determines the modification directions by the empirical Markov transition matrix of a cover image and the pseudorandom number generated by a pseudorandom number generator. The second one is based on genetic algorithm, which is used to find the optimum matching vector to make the security metric as small as possible. Experiments show the proposed algorithms outperform LSB matching and LSB replacement in a sense of the firstorder and second-order security metrics. And the adjacent calibrated COM-HCF steganalytical tests also show that the two algorithms are more secure than the traditional ones.

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