Simulating Suboptimal Steganographic Embedding

Christy Kin-Cleaves, Andrew D. Ker
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引用次数: 2

Abstract

Researchers who wish to benchmark the detectability of steganographic distortion functions typically simulate stego objects. However, the difference (coding loss) between simulated stego objects, and real stego objects is significant, and dependent on multiple factors. In this paper, we first identify some factors affecting the coding loss, then propose a method to estimate and correct for coding loss by sampling a few covers and messages. This allows us to simulate suboptimally-coded stego objects which are more accurate representations of real stego objects. We test our results against real embeddings, and naive PLS simulation, showing our simulated stego objects are closer to real embeddings in terms of both distortion and detectability. This is the case even when only a single image and message as used to estimate the loss.
模拟次优隐写嵌入
希望对隐写失真函数的可检测性进行基准测试的研究人员通常模拟隐写对象。然而,模拟隐写目标与真实隐写目标之间的差异(编码损失)是显著的,并且取决于多种因素。在本文中,我们首先识别了影响编码损失的一些因素,然后提出了一种通过采样少量封面和消息来估计和纠正编码损失的方法。这允许我们模拟次优化编码的隐写对象,这是真实隐写对象的更准确的表示。我们针对真实嵌入和朴素PLS模拟测试了我们的结果,表明我们模拟的隐写对象在失真和可检测性方面更接近真实嵌入。即使只使用单个图像和消息来估计损失也是如此。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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