基于图像像素划分的主动隐写分析
doi: 10.3724/SP.J.1146.2011.01422
Active Steganalysis Based on Pixels Classification in the Image
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摘要: 隐写分析的研究主要集中于隐写检测,而对主动隐写分析研究的较少。该文从隐写检测角度出发,将图像像素划分为不同类点,通过对信息嵌入、最低位平面置反带来的各类点频次变化的分析,提出一种针对空域图像LSB (Least Significant Bit) 替换隐写术的主动隐写分析方法,解决了主动隐写分析中的密钥恢复问题。所提出的方法物理意义直观,实现简单。实验结果表明,该方法在一定嵌入率范围内均可成功恢复隐写密钥。
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关键词:
- 隐写 /
- 隐写分析 /
- 像素划分 /
- 最低位比特(LSB)替换 /
- 密钥恢复
Abstract: The research on steganalysis has mainly focused on hidden information detection, and there are few methods about active steganalysis. From the view of hidden information detection, the pixels are classified into different kinds. Based on the analysis of the effects on the frequencies of different kinds of pixels by message embedding and Least Significant Bit (LSB) plane flipping, an active steganalysis approach is proposed to recover the stego key of LSB replacement steganography in spatial domain of images. This method has remarkable physical significance and can be implemented conveniently. Experimental results show that this method can recover the stego key successfully in certain range of embedding ratio.
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