A Robust Coverless Steganography Scheme Using Camouflage Image
A Robust Coverless Steganography Scheme Using Camouflage Image
复制标题
一种使用迷彩图像的鲁棒无盖隐写方案
DOI：
10.1109/tcsvt.2021.3108772
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发表时间：
2022-06
影响因子：
8.4
通讯作者：
Qin Zhang
中科院分区：
文献类型：
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作者：
Qiang Liu;Xuyu Xiang;Jiaohua Qin;Yun Tan;Qin Zhang
最近，大多数无覆盖图像隐写术（CIS）方法都基于稳健的映射规则。然而，由于秘密信息与哈希序列之间的映射表达关系有限，进一步提高无覆盖信息隐藏的隐藏能力是一个挑战。为了实现这一目标，本文提出了一种鲁棒的使用伪装图像的无封面隐写方案（CI-CIS）。对于发送方来说，CI-CIS引入迷彩图像作为传输载体，并通过卷积神经网络（CNN）特征建立它们之间的关联性。对于接收者来说，伪装图像可以检索相应的隐写图像来恢复秘密信息。为此，我们利用图像聚类设计了隐写图像和迷彩图像之间的可逆检索方案。同时，由于CNN表示的语义特征对图像攻击具有鲁棒性，因此我们的方法可以有效提高CIS的能力。此外，我们还建立了倒排索引来提高检索效率。实验结果和分析表明，与现有的CIS方法相比，CI-CIS具有更高的鲁棒性和更灵活的容量设置。
Recently, most coverless image steganography (CIS) methods are based on robust mapping rules. However, due to the limited mapping expression relationship between secret information and hash sequence, it is a challenge to further improve the hiding ability of coverless information hiding. Towards this goal, this paper proposes a robust coverless steganography scheme using camouflage image(CI-CIS). For the sender, CI-CIS introduces an camouflage image as the transmission carrier and establishes the correlation between them by Convolutional Neural Network(CNN) features. For the receiver, the camouflage image can retrieve the corresponding stego-image to recover the secret information. To this end, we designed a reversible retrieval scheme between stego-image and camouflage image by using image clustering. At the same time, since the semantic features represented by CNN are robust to image attacks, our method can increase the capability of the CIS effectively. Besides, we also build an inverted index to improve retrieval efficiency. Experimental results and analysis show that the CI-CIS has higher robustness and more flexible capacity setting compared with the existing CIS methods.