使用混合域技术的安全隐写

H. Reddy, N. Sathisha, A. Kumari, K. Raja
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引用次数: 13

摘要

隐写术用于隐藏信息,以安全的方式传输到目的地。本文提出了使用混合域技术(SSHDT)的安全隐写。考虑不同格式和大小的封面图像,并将其调整为2的幂次尺寸。对封面图像进行多道提升小波变换(Daubechies Lifting Wavelet transform, LWT),生成XA、XH、XV和XD四个子带。考虑了XD波段,并将其划分为上下两个相等的块,用于有效载荷嵌入。考虑不同格式的有效负载,并将其调整为2的幂维度。有效载荷被分成四个相等的块。在两个对角子带上应用整数Haar LWT生成F1和F2块,其余两个对角子带保留在空间域本身,即S1和S2。S1 S2。将F1和F2矩阵转换成单列。位反转应用于列的每个元素,以打乱有效负载索引位位置。对指标值的系数进行立方根,使数值按比例缩小。考虑将整数部分只嵌入到覆盖图像的XD波段,生成隐写目标。采用基于决策因子的操作(DFBM)对进一步的隐写对象进行置乱,以提高有效载荷的安全性。将Dubechies Inverse LWT (ILWT)应用于XA、XH、XV、XD四种隐写对象,得到空间域的隐写图像。结果表明,该算法的PSNR和嵌入容量均优于现有算法。
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Secure steganography using hybrid domain technique
The steganography is used to hide information and communicate in secure way to the destination. In this paper we propose Secure Steganography using Hybrid Domain Technique (SSHDT). The cover image of different formats and sizes are considered and resized to dimensions of power of 2. The Daubechies Lifting Wavelet Transforms (LWT) is applied on cover image to generate four sub bands XA, XH, XV and XD. The XD band is considered and divided into two equal blocks say upper and lower for payload embedding. The payload of different formats are considered and resized to dimensions of power of 2. The payload is fragmented into four equal blocks. The integer Haar LWT is applied on two diagonal sub bands to generate F1 and F2 blocks and remaining two diagonal sub bands are retained in the spatial domain itself say S1 and S2. The S1, S2. F1 and F2 matrix are converted into single columns. The bit reversal is applied on each element of a column to scramble the payload index bit positions. The cube root is applied on coefficient of index value to scale down the magnitudes. The integer part is considered for embedding in XD band only of cover image to generate stego object. The Decision Factor Based Manipulation (DFBM) is used to scramble further stego object to improve security to the payload. Dubechies Inverse LWT (ILWT) is applied on XA, XH, XV and XD stego object to obtain stego image in spatial domain. it is observed that PSNR and embedding capacity of the proposed algorithm is better compared to the existing algorithm.
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