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Towards higher detection accuracy in blind steganalysis of JPEG images

Zohourian, M ; Sharif University of Technology | 2016

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  1. Type of Document: Article
  2. DOI: 10.1109/IranianCEE.2016.7585824
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2016
  4. Abstract:
  5. A new steganalysis system for JPG-based image data hiding is proposed in this paper. We use features extracted from both wavelet and DCT domains that are refined later in the sense of utmost discrimination between the clear and stego images in the classification system. Statistical properties of the SVD of wavelet sub-bands are combined with the extended DCT-Markov features, and the features that are most sensitive to the data embedding are chosen through a SVM-RFE based selection algorithm. Experimental results show significant improvement over baseline methods, especially for steganalysis of Perturbed Quantization (PQ), which is known to be one of most secure JPG-based steganography schemes, with 90.5% average detection accuracy at low embedding rates. © 2016 IEEE
  6. Keywords:
  7. DCT ; Singular Value Decomposition ; Wavelet ; Wavelet decomposition ; Blind steganalysis ; Classification system ; Detection accuracy ; Image steganalysis ; Perturbed quantization ; Selection algorithm ; Statistical properties ; Wavelet ; Steganography
  8. Source: 24th Iranian Conference on Electrical Engineering, ICEE 2016, 10 May 2016 through 12 May 2016 ; 2016 , Pages 1860-1864 ; 9781467387897 (ISBN)
  9. URL: http://ieeexplore.ieee.org/document/7585824/?reload=true