Hide Chopin in the Music: Efficient Information Steganography Via Random Shuffling
Hide Chopin in the Music: Efficient Information Steganography Via Random Shuffling
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将肖邦隐藏在音乐中：通过随机洗牌实现高效信息隐写术
DOI：
10.1109/icassp39728.2021.9413357
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Zhao Qibin
中科院分区：
文献类型：
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作者：
Sun Zhun;Li Chao;Zhao Qibin
信息隐写术是将秘密信息隐藏到载体中的一系列技术；因此，信息只能由具有正确密钥的接收者提取，尽管已经提出了许多方法来实现这一目的，但从历史上看，隐藏大量信息而不引起人类可感知的变化是一个难题。本文探讨了自然信号（即图像、音频）的低秩特性所带来的空间，并提出了一种高效信息隐写的免训练模型，该模型提供了将全尺寸图像隐藏到相同空间分辨率的载体中的能力。该方法的关键是随机对秘密进行洗牌，并与载体进行简单的约简求和。另一方面，秘密图像可以通过求解一个类似于普通张量分解的凸优化问题来重建。在实验分析中，我们完成了两个任务：将全rgb彩色图像隐藏为灰度图像；将图像隐藏成音乐信号。结果证实了我们的模型处理大量秘密有效载荷的能力。本文的代码见https://github.com/minogame/icassp-SIC。
Information steganography is a family of techniques that hide secret messages into a carrier; thus, the messages can only be extracted by receivers with a correct key Although many approaches have been proposed to achieve this purpose, historically, it is a difficult problem to conceal a large amount of information without occasioning human perceptible changes. In this paper, we explore the room introduced by the low-rank property of natural signals (i.e., images, audios), and propose a training-free model for efficient information steganography, which provides a capacity of hiding full-size images into carriers of the same spatial resolution. The key of our method is to randomly shuffle the secrets and carry out a simple reduction summation with the carrier. On the other hand, the secret images can be reconstructed by solving a convex optimization problem similar to the ordinary tensor decomposition. In the experimental analysis, we carry out two tasks: concealing a full-RGB-color image into a gray-scale image; concealing images into music signals. The results confirm the ability of our model to handle massive secret payloads. The code of our paper is provided in https://github.com/minogame/icassp-SIC.