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A steganalysis method based on contourlet transform coefficients

Sajedi, H ; Sharif University of Technology | 2008

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  1. Type of Document: Article
  2. DOI: 10.1109/IIH-MSP.2008.11
  3. Publisher: 2008
  4. Abstract:
  5. Steganalysis is a technique to detect the presence of hidden embedded information in a given data. Each steganalyzer is composed of feature extraction and feature classification components. Using features that are more sensitive to data hiding yields higher success in steganalysis. The present paper offers a new universal approach to steganalysis that uses statistical moments of contourlet coefficients as features for analysis. A non-linear SVM classifier is used to classify cover and stego images. The effectiveness of the proposed method is demonstrated by extensive experimental investigations. The proposed steganalysis method is compared with two well known steganalyzers against typical steganography methods. The results showed the superior performance of our method. © 2008 IEEE
  6. Keywords:
  7. Cryptography ; Signal processing ; Contourlet coefficients ; Contourlet transforms ; Data hidings ; Embedded informations ; Experimental investigations ; Feature classifications ; Linear svm ; Statistical moments ; Steganalysis ; Steganography ; Stego images ; Superior performances ; Universal approaches ; Feature extraction
  8. Source: 2008 4th International Conference on Intelligent Information Hiding and Multiedia Signal Processing, IIH-MSP 2008, Harbin, 15 August 2008 through 17 August 2008 ; 2008 , Pages 245-248 ; 9780769532783 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/4604049