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Genetic algorithm based methodology for breaking the steganalytic systems

机译:基于遗传算法的打破隐写分析方法的方法

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Steganalytic techniques are used to detect whether an image contains a hidden message. By analyzing various image features between stego-images (the images containing hidden messages) and cover-images (the images containing no hidden messages), a steganalytic system is able to detect stego-images. In this paper, we present a new concept of developing a robust steganographic system by artificially counterfeiting statistic features instead of the traditional strategy by avoiding the change of statistic features. We apply genetic algorithm based methodology by adjusting gray values of a cover-image while creating the desired statistic features to generate the stego-images that can break the inspection of steganalytic systems. Experimental results show that our algorithm can not only pass the detection of current steganalytic systems, but also increase the capacity of the embedded message and enhance the peak signal-to-noise ratio of stego-images.
机译:隐写分析技术用于检测图像是否包含隐藏消息。通过分析隐身图像(包含隐藏消息的图像)和封面图像(不含隐藏消息的图像)之间的各种图像特征,隐匿分析系统能够检测到隐匿图像。在本文中,我们提出了一种新的概念,即通过人为伪造统计特征而不是通过避免统计特征发生变化的传统策略来开发鲁棒的隐写系统。我们通过调整封面图像的灰度值,同时创建所需的统计特征以生成可以破坏隐影分析系统检查的隐影图像,来应用基于遗传算法的方法。实验结果表明,该算法不仅可以通过当前隐写分析系统的检测,而且可以增加嵌入消息的容量,提高隐写图像的峰值信噪比。

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