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Multi-dimensional correlation steganalysis

Farhat, F ; Sharif University of Technology | 2011

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  1. Type of Document: Article
  2. DOI: 10.1109/MMSP.2011.6093791
  3. Publisher: 2011
  4. Abstract:
  5. Multi-dimensional spatial analysis of image pixels have not been much investigated for the steganalysis of the LSB Steganographic methods. Pixel distribution based steganalysis methods could be thwarted by intelligently compensating statistical characteristics of image pixels, as reported in several papers. Simple LSB replacement methods have been improved by introducing smarter LSB embedding approaches, e.g. LSB matching and LSB+ methods, but they are basically the same in the sense of the LSB alteration. A new analytical method to detect LSB stego images is proposed in this paper. Our approach is based on the relative locations of image pixels that are essentially changed in an LSB embedding system. Furthermore, we introduce some new statistical features including "local entropies sum" and "clouds min sum" to achieve a higher performance. Simulation results show that our proposed approach outperforms some well-known LSB steganalysis methods, in terms of detection accuracy and the embedding rate estimation
  6. Keywords:
  7. Clouds Min Sum ; Embedding Rate Estimation ; Local Entropies Sum ; LSB Embedding Steganalysis ; Multidimensional Correlation ; Analytical method ; Detection accuracy ; Embedding rates ; Image pixels ; Local entropy ; LSB embedding ; LSB matching ; LSB replacement ; LSB steganalysis ; Min-sum ; Pixel distribution ; Relative location ; Spatial analysis ; Statistical characteristics ; Statistical features ; Steganalysis ; Stego image ; Clouds ; Entropy ; Multimedia signal processing ; Signal detection ; Steganography ; Pixels
  8. Source: MMSP 2011 - IEEE International Workshop on Multimedia Signal Processing ; 2011 ; 9781457714337 (ISBN)
  9. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6093791