<![CDATA[Deep learning has been integrated with image steganography to enhance steganographic security by automatically acquiring the ability to hide information. The issue with current models is that if the cover image is accessible, it is possible to expose the hidden information by simply calculating the differences between the cover image and the steganographic image. This paper introduces a novel image steganography model that utilizes convolutional neural network (CNN) to enhance the dissimulation and extraction capabilities. Specifically, we propose a model that hides two images in a single cover image. Before being hidden within the cover image, a random pixel image is generated and combined with the real secret image. Experimental results show that our proposed method is more effective and relevant.]]>
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