基于量子生成对抗网络的信息隐藏方案

Information Hiding Scheme Based on Quantum Generative Adversarial Network

针对量子图像信息隐藏技术在面对基于统计的隐写分析算法检测时的不安全问题,提出基于量子生成对抗网络(QGAN)的信息隐藏方案.首先利用映射规则将秘密信息映射为单量子比特门,演化得到QGAN生成器G的参数化量子电路的输入态;然后通过QGAN中的生成电路生成含密量子图像;最后通过测量含密量子图像得到样本数据后与真实数据样本作为判别器D的输入进行迭代优化,使G能够得到接近于目标图像的含密图像.实验结果表明,所提方案能生成与目标图像分布较好拟合的含密图像,完成信息的非嵌入式隐藏.

Due to the insecurity of quantum image information hiding technology in the face of statistical-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 generator 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 experimental results show that proposed scheme can generate stego images that fit the target image distribution well and achieve the non-embedded hiding of information.