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Conventional steganalysis method generally encounters the problems of embedding algorithm mismatch (EAM) and cover source mismatch (CSM). These problems cause difficulties in the use of steganalysis in the real world. Learning from the idea of image pre-classified, this study presents a JPEG steganalysis paradigm combining the similarity retrieval of image-inherent statistical properties (IISP) and...
Most existing image universal steganalysis methods did not consider the impact of the differences in statistical properties among different images. This paper presents a method to improve the accuracy of JPEG universal steganalysis using image pre-classification. In the training phase, the training images are categorized into k clusters using K-means clustering according to the clustering features...
Based on the variance analysis of the noise residuals in the DCT domain, a novel blind steganalyzer is proposed for additive noise steganography in JPEG decompressed images. After investigating the influence of the data embedding on the variance and statistical distribution of DCT ac coefficients, we extract a one-dimensional feature which is the area ratio of the coefficient normalized histogram...
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