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Universal image steganalysis using singular values of DCT coefficients

Heidari, M ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1109/ISCISC.2013.6767340
  3. Publisher: IEEE Computer Society , 2013
  4. Abstract:
  5. We propose a blind image steganalysis method based on the Singular Value Decomposition (SVD) of the Discrete Cosine Transform (DCT) coefficients that are revisited in this work. We compute geometric mean, mean of log values, and statistical moments (mean, variance and skewness) of the SVDs of the DCT sub-blocks that are averaged over the whole image to construct a 480-element feature vector for steganalysis. These features are fed to a Support Vector Machine (SVM) classifier to discriminate between stego and cover images. Experimental results show that the proposed method outperforms most powerful steganalyzers when applied to some well-known steganography algorithms
  6. Keywords:
  7. Discrete cosine transform (DCT) ; Image steganalysis ; Singular value decomposition (SVD) ; Cryptography ; Discrete cosine transforms ; Image analysis ; Image retrieval ; Steganography ; Support vector machines ; Blind image steganalysis ; DCT coefficients ; Discrete cosine transform coefficients ; Feature vectors ; Singular values ; Statistical moments ; Singular value decomposition
  8. Source: 2013 10th International ISC Conference on Information Security and Cryptology ; 2013
  9. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6767340