Steganalysis of ±k Steganography based on Noncausal Linear Predictor

K. Manglem Singh, Yambem Jina Chanu, Themrichon Tuithung


The paper proposes a novel steganalytic technique for ±k steganography
based on noncausal linear predictor using prediction coefficients obtained from the autocorrelation
matrix for a block of pixels in the stego-image. The image is divided into
equal-size blocks, autocorrelation matrix is found for the block, and the appropriate
noncausal linear prediction coefficients is selected to predict all pixels in that block. A
pixel is assumed to be embedded with message bit if the absolute difference between
the original pixel value and predicted pixel value exceeds the pre-defined threshold.
The effectiveness of the proposed technique is verified using different images.


LSB embedding, noncausal linear predictor, RS analysis, steganalysis, steganography

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