Improving Selection-Channel-Aware Steganalysis Features

@inproceedings{Denemark2016ImprovingSS,
  title={Improving Selection-Channel-Aware Steganalysis Features},
  author={Tom{\'a}s Denemark and Jessica J. Fridrich and Pedro Comesa{\~n}a Alfaro},
  booktitle={Media Watermarking, Security, and Forensics},
  year={2016}
}
Currently, the best detectors of content-adaptive steganography are built as classifiers trained on examples of cover and stego images represented with rich media models (features) formed by histograms (or co-occurrences) of quantized noise residuals. Recently, it has been shown that adaptive steganography can be more accurately detected by incorporating content adaptivity within the features by accumulating the embedding change probabilities (change rates) in the histograms. However, because… CONTINUE READING

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