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Image steganalysis based on SVD and noise estimation: Improve sensitivity to spatial LSB embedding families

Diyanat, A ; Sharif University of Technology | 2011

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  1. Type of Document: Article
  2. DOI: 10.1109/TENCON.2011.6129010
  3. Publisher: 2011
  4. Abstract:
  5. We propose a novel image steganalysis method, based on singular value decomposition and noise estimation, for the spatial domain LSB embedding families. We first define a content independence parameter, DS, that is calculated for each LSB embedding rate. Next, we estimate the DS curve and use noise estimation to improve the curve approximation accuracy. It is shown that the proposed approach gives an estimate of the LSB embedding rate, as well as information about the existence of the embedded message (if any). The proposed method can effectively be applied to a wide range of the image LSB steganography families in spatial domain. To evaluate the proposed scheme, we applied the method to a large image database. Using a large image database, simulation results of our steganalysis scheme indicate significant improvement to both true detection and false alarm rates
  6. Keywords:
  7. Curve approximation ; Embedded messages ; False alarm rate ; Large image database ; LSB embedding ; LSB steganography ; Noise estimation ; Singular value Decomposition (SVD) ; Spatial domains ; Steganalysis ; Image analysis ; Steganography ; Singular value decomposition
  8. Source: IEEE Region 10 Annual International Conference, Proceedings/TENCON, 21 November 2011 through 24 November 2011, Bali ; 2011 , Pages 1266-1270 ; 9781457702556 (ISBN)
  9. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6129010