A Hidden Information Blind Detection Method Based on Rough Set Theory

For improving the detection efficiency of hidden information blind detection system, an improved hidden information detection method based rough set theory is proposed against the high dimension of statistical features and high relevance about images. First, an improved general steganalysis system framework is proposed with practical method and steps; second, the Algorithm based on the rough set theory reduces feature dimension, computational complexity of classification, and eliminates the relevance among statistical features; third, the realization procedure is offered in this algorithm; the SVM classifier is employed to test the spread spectrums steganalysis Cox and Piva. And the large body of experimental results proves that the algorithm is correct and with a higher time efficiency and accuracy than Shi´s and the method mentioned in reference.