Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (67)
  • Open Access

    ARTICLE

    A Survey of Image Information Hiding Algorithms Based on Deep Learning

    Ruohan Meng1,2,*, Qi Cui1,2, Chengsheng Yuan1,2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.3, pp. 425-454, 2018, DOI:10.31614/cmes.2018.04765

    Abstract With the development of data science and technology, information security has been further concerned. In order to solve privacy problems such as personal privacy being peeped and copyright being infringed, information hiding algorithms has been developed. Image information hiding is to make use of the redundancy of the cover image to hide secret information in it. Ensuring that the stego image cannot be distinguished from the cover image, and sending secret information to receiver through the transmission of the stego image. At present, the model based on deep learning is also widely applied to the field of information hiding. This… More >

  • Open Access

    ARTICLE

    Locating Steganalysis of LSB Matching Based on Spatial and Wavelet Filter Fusion

    Chunfang Yang1,*, Jie Wang1, Chengliang Lin1, Huiqin Chen2, Wenjuan Wang1

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 633-644, 2019, DOI:10.32604/cmc.2019.06154

    Abstract For the case of that only a single stego image of LSB (Least Significant Bit) matching steganography is available, the existing steganalysis algorithms cannot effectively locate the modified pixels. Therefore, an algorithm is proposed to locate the modified pixels of LSB matching based on spatial and wavelet filter fusion. Firstly, the validity of using the residuals obtained by spatial and wavelet filtering to locate the modified pixels of LSB matching is analyzed. It is pointed out that both of these two kinds of residuals can be used to identify the modified pixels of LSB matching with success rate higher than… More >

  • Open Access

    ARTICLE

    Embedding Image Through Generated Intermediate Medium Using Deep Convolutional Generative Adversarial Network

    Chuanlong Li1,2,*, Yumeng Jiang3, Marta Cheslyar1

    CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 313-324, 2018, DOI: 10.3970/cmc.2018.03950

    Abstract Deep neural network has proven to be very effective in computer vision fields. Deep convolutional network can learn the most suitable features of certain images without specific measure functions and outperform lots of traditional image processing methods. Generative adversarial network (GAN) is becoming one of the highlights among these deep neural networks. GAN is capable of generating realistic images which are imperceptible to the human vision system so that the generated images can be directly used as intermediate medium for many tasks. One promising application of using GAN generated images would be image concealing which requires the embedded image looks… More >

  • Open Access

    ARTICLE

    Coverless Steganography for Digital Images Based on a Generative Model

    Xintao Duan1,*, Haoxian Song1, Chuan Qin2, Muhammad Khurram Khan3

    CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 483-493, 2018, DOI: 10.3970/cmc.2018.01798

    Abstract 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.… More >

  • Open Access

    ARTICLE

    Steganography Using Reversible Texture Synthesis Based on Seeded Region Growing and LSB

    Qili Zhou1, Yongbin Qiu1, Li Li1,*, Jianfeng Lu1, Wenqiang Yuan1, Xiaoqing Feng2, Xiaoyang Mao3

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 151-163, 2018, DOI:10.3970/cmc.2018.055.151

    Abstract Steganography technology has been widely used in data transmission with secret information. However, the existing steganography has the disadvantages of low hidden information capacity, poor visual effect of cover images, and is hard to guarantee security. To solve these problems, steganography using reversible texture synthesis based on seeded region growing and LSB is proposed. Secret information is embedded in the process of synthesizing texture image from the existing natural texture. Firstly, we refine the visual effect. Abnormality of synthetic texture cannot be fully prevented if no approach of controlling visual effect is applied in the process of generating synthetic texture.… More >

  • Open Access

    ARTICLE

    Defining Embedding Distortion for Intra Prediction Mode-Based Video Steganography

    Qiankai Nie1, Xuba Xu1, Bingwen Feng1,*, Leo Yu Zhang2

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 59-70, 2018, DOI:10.3970/cmc.2018.055.059

    Abstract In this paper, an effective intra prediction mode-based video strganography is proposed. Secret messages are embedded during the intra prediction of the video encoding without causing large embedding impact. The influence on the sum of absolute difference (SAD) in intra prediction modes (IPMs) reversion phenomenon is sharp when modifying IPMs. It inspires us to take the SAD prediction deviation (SPD) to define the distortion function. What is more, the mapping rule between IPMs and the codewords is introduced to further reduce the SPD values of each intra block. Syndrome-trellis code (STC) is used as the practical embedding implementation. Experimental results… More >

  • Open Access

    ARTICLE

    A Fusion Steganographic Algorithm Based on Faster R-CNN

    Ruohan Meng1,2, Steven G. Rice3, Jin Wang4, Xingming Sun1,2,*

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 1-16, 2018, DOI:10.3970/cmc.2018.055.001

    Abstract The aim of information hiding is to embed the secret message in a normal cover media such as image, video, voice or text, and then the secret message is transmitted through the transmission of the cover media. The secret message should not be damaged on the process of the cover media. In order to ensure the invisibility of secret message, complex texture objects should be chosen for embedding information. In this paper, an approach which corresponds multiple steganographic algorithms to complex texture objects was presented for hiding secret message. Firstly, complex texture regions are selected based on a kind of… More >

Displaying 61-70 on page 7 of 67. Per Page