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Reduced complexity enhancement of steganalysis of LSB-matching image steganography

Malekmohamadi, H ; Sharif University of Technology | 2009

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  1. Type of Document: Article
  2. DOI: 10.1109/AICCSA.2009.5069455
  3. Publisher: 2009
  4. Abstract:
  5. We propose a method for steganalysis of still, grayscale images using a novel set of features that are extracted from images. This feature set employs the Gabor filter coefficients to train a multi-layer perceptron neural network and a support vector machine classifier. We show that incorporation of the Gabor filter coefficients to the feature sets of images could have a significant role in discrimination between clean and altered images. Experimental results show that the proposed method outperforms previous methods, introduced for steganalysis of LSB-matching image steganography, in terms of both discrimination accuracy and feature set dimensionality. © 2009 IEEE
  6. Keywords:
  7. Discrimination accuracy ; Feature sets ; Gabor filter ; Gray-scale images ; Image steganography ; Multi-layer perceptron neural networks ; Reduced complexity ; Steganalysis ; Cryptography ; Image processing
  8. Source: 7th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA-2009, Rabat, 10 May 2009 through 13 May 2009 ; 2009 , Pages 1013-1017 ; 9781424438068 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/5069455