Steganographic coding scheme based on dither convolutional trellis under resampling mechanism

Abstract

With the rapid development of mobile internet and cloud computing, numerous digital me-dia files in mobile social networking and media sharing software have become the important carriers of steganography. However, these digital media files may be resampled by the media server when being pushed to the intelligent mobile terminals. The resampling of digital media files is a transfor-mation which enlarges or shrinks objects by a scale factor that is the same in all dimensions. In order to reduce embedding distortion while ensuring the correct extraction of secret messages under resam-pling mechanism, a steganographic coding scheme based on dither convolutional trellis is proposed in this paper. The resampling mapping is estimated with finite sample pairs. The resampling stego media files with secret messages embedded are generated from the estimated resampling cover media files by syndrome-trellis codes (STCs). According to the estimated resampling mapping, the dither convolutional trellis for one dimensional resampling is constructed to generate the source stego me-dia files from source cover media files and resampling stego media files. The steganographic coding scheme is also extended to the circumstance of two dimensional resampling such as image scaling. The experimental results show that the proposed steganographic scheme can achieve less embedding dis-tortion while ensuring the accuracy of secret messages extraction under multi-dimensional resampling mechanism.

Keywords

• steganographic coding
• multi-dimensional resampling
• resampling mapping estimation
• dither convolution trellis