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  • Open Access

    ARTICLE

    An Image Steganography Algorithm Based on Quantization Index Modulation Resisting Scaling Attacks and Statistical Detection

    Yue Zhang1, Dengpan Ye2, Junjun Gan1, Zhenyu Li3, Qingfeng Cheng1,*

    CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 151-167, 2018, DOI: 10.3970/cmc.2018.02464

    Abstract In view of the fact that the current adaptive steganography algorithms are difficult to resist scaling attacks and that a method resisting scaling attack is only for the nearest neighbor interpolation method, this paper proposes an image steganography algorithm based on quantization index modulation resisting both scaling attacks and statistical detection. For the spatial image, this paper uses the watermarking algorithm based on quantization index modulation to extract the embedded domain. Then construct the embedding distortion function of the new embedded domain based on S-UNIWARD steganography, and use the minimum distortion coding to realize the embedding of the secret messages.… More >

  • Open Access

    ARTICLE

    A Novel Quantum Stegonagraphy Based on Brown States

    Zhiguo Qu1,*, Tiancheng Zhu2, Jinwei Wang1, Xiaojun Wang3

    CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 47-59, 2018, DOI: 10.3970/cmc.2018.02215

    Abstract In this paper, a novel quantum steganography protocol based on Brown entangled states is proposed. The new protocol adopts the CNOT operation to achieve the transmission of secret information by the best use of the characteristics of entangled states. Comparing with the previous quantum steganography algorithms, the new protocol focuses on its anti-noise capability for the phase-flip noise, which proved its good security resisting on quantum noise. Furthermore, the covert communication of secret information in the quantum secure direct communication channel would not affect the normal information transmission process due to the new protocol’s good imperceptibility. If the number of… More >

  • Open Access

    ARTICLE

    On Hiding Secret Information in Medium Frequency DCT Components Using Least Significant Bits Steganography

    Sahib Khan1,*, M A Irfan1, Arslan Arif1, Syed Tahir Hussain Rizvi2, Asma Gul3, Muhammad Naeem4, Nasir Ahmad5

    CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.3, pp. 529-546, 2019, DOI:10.31614/cmes.2019.06179

    Abstract This work presents a new method of data hiding in digital images, in discrete cosine transform domain. The proposed method uses the least significant bits of the medium frequency components of the cover image for hiding the secret information, while the low and high frequency coefficients are kept unaltered. The unaltered low frequency DCT coefficients preserves the quality of the smooth region of the cover image, while no changes in the high DCT coefficient preserve the quality of the edges. As the medium frequency components have less contribution towards energy and image details, so the modification of these coefficients for… More >

  • 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 >

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