基于量子生成对抗网络的信息隐藏方案

Q3 Computer Science
Jia Luo, Rigui Zhou, Yaochong Li, Guangzhong Liu
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引用次数: 2

摘要

针对量子图像信息隐藏技术在面对基于统计量的隐写算法检测时存在的不安全性,提出了一种基于量子生成对抗网络(QGAN)的信息隐藏方案。该方案首先利用映射规则将秘密信息映射到单量子比特门,为发生器G的参数化量子电路的输入状态做准备。然后通过QGAN中的生成电路生成隐存量子图像。最后,将测量隐写图像得到的样本数据和真实数据作为鉴别器D的输入。进行迭代优化,使G能得到接近目标图像的隐进图像。实验结果表明,该方法能够生成符合目标图像分布的隐写图像,实现了信息的非嵌入隐藏。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Information Hiding Scheme Based on Quantum Generative Adversarial Network
: Due to the insecurity of quantum image information hiding technology in the face of statisti-cal-based steganalysis algorithm detection, an information hiding scheme based on quantum generative adversarial network (QGAN) is proposed. This scheme first uses the mapping rules to map the secret information into the single qubit gate to prepare for the input state of the parameterized quantum circuit of the gen-erator G . Then the stego quantum image is generated by the generating circuit in QGAN. Finally, the sample data obtained by measuring the stego image and the real data are used as the input of the discriminator D . The iterative optimization is performed so that G can obtain a stego image close to the target image. The ex-perimental results show that proposed scheme can generate stego images that fit the target image distribution well and achieve the non-embedded hiding of information.
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来源期刊
计算机辅助设计与图形学学报
计算机辅助设计与图形学学报 Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
1.20
自引率
0.00%
发文量
6833
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