In this paper,we propose a novel coverless image steganographic scheme based on a generative model.In our scheme,the secret image is first fed to the generative model database,to generate a meaning-normal and independ...In this paper,we propose a novel coverless image steganographic scheme based on a generative model.In our scheme,the secret image is first fed to the generative model database,to generate a meaning-normal and independent image different from the secret image.The generated image is then transmitted to the receiver and fed to the generative model database to generate another image visually the same as the secret image.Thus,we only need to transmit the meaning-normal image which is not related to the secret image,and we can achieve the same effect as the transmission of the secret image.This is the first time to propose the coverless image information steganographic scheme based on generative model,compared with the traditional image steganography.The transmitted image is not embedded with any information of the secret image in this method,therefore,can effectively resist steganalysis tools.Experimental results show that our scheme has high capacity,security and reliability.展开更多
In order to estimate maximum steganographic capacity of discrete cosine transform（DCT） domain in JPEG image, this paper presents a method based on the maximize capacity under undetectable model（MCUU）. We analyze t...In order to estimate maximum steganographic capacity of discrete cosine transform（DCT） domain in JPEG image, this paper presents a method based on the maximize capacity under undetectable model（MCUU）. We analyze the relation between steganographic capacity and affecting factors（image size, steganography operator, loading band, embedding intensity and image complexity）. Then we design a steganography analyzer architecture and a steganographic algorithm which can dynamically increase the steganographic capacity. Compared with other methods of embedding capacity estimation in DCT domain, the proposed methods utilizes general steganalysis methods rather than one specific steganalysis technique and takes five essential factors into account, which improves the commonality and comprehensiveness of capacity estimation, respectively. The experimental results show that steganographic capacity for quantization index modulation（QIM） is almost twice that of spread spectrum（SS） based on MCUU model.展开更多
基金This paper was supported by the National Natural Science Foundation of China(No.U1204606)the Key Programs for Science and Technology Development of Henan Province(No.172102210335)Key Scientific Research Projects in Henan Universities(No.16A520058).
文摘In this paper,we propose a novel coverless image steganographic scheme based on a generative model.In our scheme,the secret image is first fed to the generative model database,to generate a meaning-normal and independent image different from the secret image.The generated image is then transmitted to the receiver and fed to the generative model database to generate another image visually the same as the secret image.Thus,we only need to transmit the meaning-normal image which is not related to the secret image,and we can achieve the same effect as the transmission of the secret image.This is the first time to propose the coverless image information steganographic scheme based on generative model,compared with the traditional image steganography.The transmitted image is not embedded with any information of the secret image in this method,therefore,can effectively resist steganalysis tools.Experimental results show that our scheme has high capacity,security and reliability.
基金Supported by the National Natural Science Foundation of China(61170271,61170272,61272310,61373131,61573316)Zhejiang Provincial Natural Science Foundation of China(LY15F020032,LQ12 F02016,LQ15E050006)
文摘In order to estimate maximum steganographic capacity of discrete cosine transform（DCT） domain in JPEG image, this paper presents a method based on the maximize capacity under undetectable model（MCUU）. We analyze the relation between steganographic capacity and affecting factors（image size, steganography operator, loading band, embedding intensity and image complexity）. Then we design a steganography analyzer architecture and a steganographic algorithm which can dynamically increase the steganographic capacity. Compared with other methods of embedding capacity estimation in DCT domain, the proposed methods utilizes general steganalysis methods rather than one specific steganalysis technique and takes five essential factors into account, which improves the commonality and comprehensiveness of capacity estimation, respectively. The experimental results show that steganographic capacity for quantization index modulation（QIM） is almost twice that of spread spectrum（SS） based on MCUU model.
