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首页> 外文期刊>International Journal of Innovative Computing Information and Control >A NOVEL HIGH CAPACITY 3D STEGANOGRAPHIC ALGORITHM
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A NOVEL HIGH CAPACITY 3D STEGANOGRAPHIC ALGORITHM

机译：新型的高容量3D隐写算法

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This paper presents a powerful high capacity 3D steganographic algorithm which can embed more than 9.6 million bits of a secret message using a 3D polygon model with only 14,004 vertices. To the best of our knowledge, this is the largest capacity ever reported in the literature. We accomplish this novel algorithm by using two levels of message encoding. In the first level, we subdivide the secret message into a number of payload fragments. We then encode each payload fragment by utilizing a corresponding random sample generated on a unit sphere. In the second level, we encode these random samples to a number of feature points which convey the payload fragment and are skillfully located on the surface of an existing 3D polygon model. The procedure produces a point cloud stego model that can be delivered in a public channel for steganographic purposes. We produce dummy points by uniform sampling over the surface area of the 3D polygon model which increases the rendering quality of the point cloud stego model and also prevents suspicion of the messages by eavesdroppers. Our scheme has five features. First, it can embed a significantly large number of payloads using 3D polygonal models with small complexity. Theoretical analysis indicates that our algorithm has a significantly high capacity with the magnitude of 50 bits per feature point, outperforming that offered by the current state-of-the-art 3D steganographic algorithms. Second, the scheme is flexible, allowing it to convey various capacities by adjusting two region partition parameters. Third, it belongs to a distortion-free manner, and encounters no model variation because of the hidden message. Fourth, the algorithm belongs to a blind extraction, enabling it to extract the secret message without referring to the original cover model. Finally, the scheme provides independency for the secret payload embedding and supports progressive message extraction.
机译：本文提出了一种强大的高容量3D隐写算法，该算法可以使用仅包含14,004个顶点的3D多边形模型来嵌入960万比特的秘密消息。据我们所知，这是文献中报道的最大容量。我们通过使用两个级别的消息编码来完成这种新颖的算法。在第一级中，我们将秘密消息细分为许多有效载荷片段。然后，我们利用在单位球体上生成的相应随机样本对每个有效载荷片段进行编码。在第二级中，我们将这些随机样本编码为多个特征点，这些特征点传达有​​效载荷片段，并巧妙地位于现有3D多边形模型的表面上。该过程将生成一个点云隐身模型，可以将其在公共渠道中交付以进行隐写。我们通过在3D多边形模型的表面上进行均匀采样来生成虚拟点，这不仅提高了点云隐身模型的渲染质量，而且还防止了窃听者对消息的怀疑。我们的方案有五个特点。首先，它可以使用复杂度较小的3D多边形模型嵌入大量有效负载。理论分析表明，我们的算法具有很高的容量，每个特征点的大小为50位，远胜过当前最新的3D隐写算法。其次，该方案非常灵活，可以通过调整两个区域分区参数来传达各种容量。第三，它属于无失真方式，并且由于隐藏消息而不会遇到模型变化。第四，该算法属于盲提取，使它无需参考原始掩盖模型即可提取秘密消息。最后，该方案为秘密有效载荷嵌入提供了独立性，并支持渐进式消息提取。

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