Revisiting weighted stego-image steganalysis

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Abstract
This paper revisits the steganalysis method involving a Weighted Stego-Image (WS) for estimating LSB replacement payload sizes in digital images. It suggests new WS estimators, upgrading the method's three components: cover pixel prediction, least-squares weighting, and bias correction. Wide-ranging experimental results (over two million total attacks) based on images from multiple sources and pre-processing histories show that the new methods produce greatly improved accuracy, to the extent that they outperform even the best of the structural detectors, while avoiding their high complexity. Furthermore, specialised WS estimators can be derived for detection of sequentially-placed payload: they offer levels of accuracy orders of magnitude better than their competitors.

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