基于StarGAN的生成式图像隐写方案

doi:10.3969/j.issn.1671-1122.2020.12.009

信息网络安全 ›› 2020, Vol. 20 ›› Issue (12): 64-71.doi: 10.3969/j.issn.1671-1122.2020.12.009

基于StarGAN的生成式图像隐写方案

毕新亮¹^,², 杨海滨¹, 杨晓元¹^,²(), 黄思远¹

1.武警工程大学密码工程学院,西安 710086
2.网络与信息安全武警部队重点实验室,西安 710086

收稿日期:2020-09-27 出版日期:2020-12-10 发布日期:2021-01-12
通讯作者: 杨晓元 E-mail:gcxy_xxyc@126.com
作者简介:毕新亮（1997—）,男,安徽,硕士研究生,主要研究方向为深度学习、信息隐藏|杨海滨（1982—）,男,河北,讲师,博士,主要研究方向为密码学、信息安全|杨晓元（1959—）,男,湖南,教授,硕士,主要研究方向为密码学、信息隐藏|黄思远（1997—）,男,陕西,硕士研究生,主要研究方向为深度学习、隐写分析
基金资助:
国家自然科学基金(61872384)

Generative Steganography Scheme Based on StarGAN

BI Xinliang¹^,², YANG Haibin¹, YANG Xiaoyuan¹^,²(), HUANG Siyuan¹

1. College of Cryptographic Engineering, Engineering University of PAP, Xi’an 710086, China
2. Network and Information Security Key Laboratory of PAP, Xi’an 710086, China

Received:2020-09-27 Online:2020-12-10 Published:2021-01-12
Contact: YANG Xiaoyuan E-mail:gcxy_xxyc@126.com

摘要/Abstract

摘要：

针对生成式隐写存在的生成图像与真实图像相差较大、图像翻译隐写需要训练大量模型等问题,文章提出了基于StarGAN的生成式图像隐写方案。该方案仅需一个模型即可完成多风格图像翻译任务。发送方将秘密信息进行编码,映射为图像的风格标签,然后生成相应风格的图像,发送给接收方;接收方使用秘密信道传递的提取模型,对图像进行风格标签的提取,并对照编码方式解码出秘密消息。实验结果表明,该方案在减少训练模型数量的同时,图像质量、消息提取准确性等方面均有明显提升。

关键词: 信息隐藏, 深度学习, 生成式图像隐写, 图像翻译

Abstract:

Aiming at the problems that the generated image and the real image are different in the generative steganography, and the image translation steganography needs to train a large number of models, a generative image steganography scheme based on StarGAN is proposed. Only one model can complete multi-style image translation task. The sender encodes the secret information, maps it to the style tag of the image, generates an image of the corresponding style, and sends it to the receiver. The receiver uses the extraction model which passed by the secret channel to extract the style tag of the image, and compares the encoding method to decode the secret informatione. The experimental results show that while reducing the number of training models, the scheme has significantly improved image quality and information extraction accuracy.

Key words: information hiding, deep learning, generative steganography, image translation

中图分类号:

TP309

毕新亮, 杨海滨, 杨晓元, 黄思远. 基于StarGAN的生成式图像隐写方案[J]. 信息网络安全, 2020, 20(12): 64-71.

BI Xinliang, YANG Haibin, YANG Xiaoyuan, HUANG Siyuan. Generative Steganography Scheme Based on StarGAN[J]. Netinfo Security, 2020, 20(12): 64-71.

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参考文献 21

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	大嘴唇	双下巴	山羊胡子	年轻	···	刘海
风格标签码	1	-1	-1	1	···	-1
秘密消息	1	0	0	1	···	0
风格标签码	1	-1	-1	1	···	-1
秘密消息	1	0	0	1	···	0
风格标签码	1	-1	-1	1	···	1
秘密消息	1	0	0	1	···	1
风格标签码	-1	-1	-1	1	···	-1
秘密消息	0	0	0	1	···	0

网络名称	转换风格类别	需要模型数
IcGAN	2	2
CycleGAN	2	2
本文方案	2	1
IcGAN	3	6
CycleGAN	3	6
本文方案	3	1

网络名称	FID值
IcGAN	155.5442
CycleGAN	45.3995
本文方案	34.6783

方法	提取准确率
文献[9]	89.3%-96.0%
本文方案（64×64）	88.6%
本文方案（128×128）	95.0%

基于StarGAN的生成式图像隐写方案

Generative Steganography Scheme Based on StarGAN

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