A new secure adaptive steganographic algorithm using Fibonacci numbers

S. Agaian, Ravindranath Cherukuri, Ronnie R. Sifuentes
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引用次数: 15

Abstract

In this paper, we investigate the common problems encountered in adaptive steganography. The focus of these systems is on security and thus capacity is severely limited. An algorithm combining T-order statistics with Fibonacci based image decomposition is introduced. As the T-order statistics enables the embedding of secret data only in the noisy regions making any changes to the cover undetectable. The decomposition of an image based on Fibonacci numbers creates a higher number of bit planes compared to the 8 associated with traditional image decomposition. As a result, the distribution of data over an increased number of bit layers enhances the available capacity. In addition, the impact caused by image modifications necessary when embedding secret information is reduced. Computer simulations were performed over 50 color and 50 grayscale bitmap images varying in size, color, and classes of image features. In comparison with other existing adaptive and non-adaptive embedding methods, the proposed method shows a greater resistance to detection against various steganalysis tools while offering a marked increase in available capacity.
一种基于斐波那契数的安全自适应隐写算法
本文研究了自适应隐写术中常见的问题。这些系统的重点是安全,因此能力受到严重限制。介绍了一种基于t阶统计量和斐波那契的图像分解算法。由于t阶统计量只允许在噪声区域内嵌入秘密数据,使得覆盖的任何变化都无法检测到。基于斐波那契数的图像分解与传统图像分解相关的8个位平面相比,创建了更多的位平面。因此,数据在越来越多的位层上的分布增强了可用容量。此外,还减少了嵌入秘密信息时需要对图像进行修改所带来的影响。计算机模拟了50张彩色和50张灰度位图图像,这些图像在大小、颜色和图像特征类别上有所不同。与其他现有的自适应和非自适应嵌入方法相比,所提出的方法对各种隐写分析工具的检测具有更大的抵抗力,同时提供了显著增加的可用容量。
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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