Batch Zero-steganographic Model for Graph Transformation

نویسندگان

  • Gouxi Chen
  • Pengcheng Zhang
  • Meng Zhang
  • Yuliang Wu
چکیده

To further improve the security of digital image steganography, based on graph transformation diversity, proposed a zero-steganographic model. After divided into many blocks, the secret information is deduced by graphic transform algorithm, and a cover image steganographic model for not carrying secret information is constructed. First step is selecting a batch of cover images through a particular transformation algorithm for them, and then find out the correlation of pixels between secret images and the new images, finally return to its original for transmission. Extracting secret information only to need the key without carrier images, further improve the security of secret information. Experimental results and analysis show that this model confidential is strong, the security is good, and applies to images concealed communication.

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تاریخ انتشار 2012