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Revisiting Weighted Stego-Image Steganalysis

机译:再谈加权隐身图像隐写分析

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摘要

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.
机译:本文重新审视了包含加权隐身图像(WS)的隐写分析方法,以估计数字图像中LSB替换有效载荷的大小。它建议使用新的WS估计器,升级方法的三个组成部分:覆盖像素预测,最小二乘加权和偏差校正。基于来自多个来源的图像和预处理历史的广泛实验结果(总计超过200万次攻击)表明,新方法的准确性大大提高,以至于它们甚至超过了最好的结构探测器,同时又避免了它们的使用。高复杂度。此外,可以导出专用的WS估计器来检测顺序放置的有效负载:它们提供的精度水平要比其竞争对手好几个数量级。

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