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Steganalytic features for JPEG compression-based perturbed quantization
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DOI：10.1109/LSP.2006.884010.png)
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Abstract
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Perturbed quantization (PQ) data hiding is almost undetectable with the current steganalysis methods. We briefly describe PQ and propose singular value decomposition (SVD)-based features for the steganalysis of JPEG-based PQ data hiding in images. We show that JPEG-based PQ data hiding distorts linear dependencies of rows/columns of pixel values, and proposed features can be exploited within a simple classifier for the steganalysis of PQ. The proposed steganalyzer detects PQ embedding on relatively smooth stego images with 70% detection accuracy on average for different embedding rates.
Keywords:
singular value decomposition (SVD)
steganalysis
steganography
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