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HYSA: HYbrid steganographic approach using multiple steganography methods

Sajedi, H ; Sharif University of Technology | 2011

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  1. Type of Document: Article
  2. DOI: 10.1002/sec.243
  3. Publisher: John Wiley and Sons Inc , 2011
  4. Abstract:
  5. The aim of image steganography is to hide data in an image with visual and statistical invisibility. There have been a number of steganography techniques proposed over the past few years. In sequence, the development of these methods has led to an increased interest in steganalysis techniques. Most of the steganalysis methods attempt to estimate cover image statistics. One way to provide a secure steganography method is to disturb the estimation of steganalyzers. The main concern of this paper is to resist against steganalysis methods and utilize a mechanism to securely embed more secret data into an image. We present HYbrid steganographic approach (HYSA), which embeds secret data with randomized embedding algorithms in randomized regions of the cover image. HYSA embeds secret data in only some regions of the image not all over the image. In addition, HYSA can employ more than one steganography method for embedding secret data in the image. Random selection of embedding regions and steganography methods leaves a combination of several types of distortion on the image, which are difficult to be recognized by the steganalysis methods. Experimental results by applying some well-known and efficient steganalysis methods illustrate that the proposed steganographic approach is more undetectable than some popular steganography methods
  6. Keywords:
  7. Cover-image ; Covert communications ; Embedding algorithms ; Image steganography ; Information hiding ; Random selection ; Randomized hiding ; Secret data ; Secure steganography ; Statistical invisibility ; Steganalysis ; Steganography
  8. Source: Security and Communication Networks ; Volume 4, Issue 10 , OCT , 2011 , Pages 1173-1184 ; 19390114 (ISSN)
  9. URL: http://onlinelibrary.wiley.com/doi/10.1002/sec.243/abstract;jsessionid=05735C7A30A6F67625E5DC60DAEDBDCA.f04t04