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Search Results (19)
  • Open Access

    ARTICLE

    An Efficient Steganalysis Model Based on Multi-Scale LTP and Derivative Filters

    Yuwei Chen1, 2, Yuling Chen1, *, Yu Yang1, 2, Xinda Hao2, Ning Wang2

    CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1259-1271, 2020, DOI:10.32604/cmc.2020.06723

    Abstract Local binary pattern (LBP) is one of the most advanced image classification recognition operators and is commonly used in texture detection area. Research indicates that LBP also has a good application prospect in steganalysis. However, the existing LBP-based steganalysis algorithms are only capable to detect the least significant bit (LSB) and the least significant bit matching (LSBM) algorithms. To solve this problem, this paper proposes a steganalysis model called msdeLTP, which is based on multi-scale local ternary patterns (LTP) and derivative filters. The main characteristics of the msdeLTP are as follows: First, to reduce the interference of image content on… More >

  • Open Access

    ARTICLE

    An Adaptive Image Calibration Algorithm for Steganalysis

    Xuyu Xiang1, Jiaohua Qin1, *, Junshan Tan1, Neal N. Xiong1

    CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 963-976, 2020, DOI:10.32604/cmc.2020.06394

    Abstract In this paper, a new adaptive calibration algorithm for image steganalysis is proposed. Steganography disturbs the dependence between neighboring pixels and decreases the neighborhood node degree. Firstly, we analyzed the effect of steganography on the neighborhood node degree of cover images. Then, the calibratable pixels are marked by the analysis of neighborhood node degree. Finally, the strong correlation calibration image is constructed by revising the calibratable pixels. Experimental results reveal that compared with secondary steganography the image calibration method significantly increased the detection accuracy for LSB matching steganography on low embedding ratio. The proposed method also has a better performance… More >

  • Open Access

    ARTICLE

    A HEVC Video Steganalysis Algorithm Based on PU Partition Modes

    Zhonghao Li1, Laijin Meng1, Shutong Xu1, Zhaohong Li1,2,*, Yunqing Shi3, Yuanchang Liang1

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 563-574, 2019, DOI:10.32604/cmc.2019.05565

    Abstract Steganalysis is a technique used for detecting the existence of secret information embedded into cover media such as images and videos. Currently, with the higher speed of the Internet, videos have become a kind of main methods for transferring information. The latest video coding standard High Efficiency Video Coding (HEVC) shows better coding performance compared with the H.264/AVC standard published in the previous time. Therefore, since the HEVC was published, HEVC videos have been widely used as carriers of hidden information.
    In this paper, a steganalysis algorithm is proposed to detect the latest HEVC video steganography method which is based… More >

  • Open Access

    ARTICLE

    Color Image Steganalysis Based on Residuals of Channel Differences

    Yuhan Kang1, Fenlin Liu1, Chunfang Yang1,*, Xiangyang Luo1, Tingting Zhang2

    CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 315-329, 2019, DOI:10.32604/cmc.2019.05242

    Abstract This study proposes a color image steganalysis algorithm that extracts high-dimensional rich model features from the residuals of channel differences. First, the advantages of features extracted from channel differences are analyzed, and it shown that features extracted in this manner should be able to detect color stego images more effectively. A steganalysis feature extraction method based on channel differences is then proposed, and used to improve two types of typical color image steganalysis features. The improved features are combined with existing color image steganalysis features, and the ensemble classifiers are trained to detect color stego images. The experimental results indicate… 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

    A Novel Universal Steganalysis Algorithm Based on the IQM and the SRM

    Yu Yang1,2,*, Yuwei Chen1,2, Yuling Chen2, Wei Bi3,4

    CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 261-272, 2018, DOI: 10.3970/cmc.2018.02736

    Abstract The state-of-the-art universal steganalysis method, spatial rich model (SRM), and the steganalysis method using image quality metrics (IQM) are both based on image residuals, while they use 34671 and 10 features respectively. This paper proposes a novel steganalysis scheme that combines their advantages in two ways. First, filters used in the IQM are designed according to the models of the SRM owning to their strong abilities for detecting the content adaptive steganographic methods. In addition, a total variant (TV) filter is also used due to its good performance of preserving image edge properties during filtering. Second, due to each type… 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

    Binary Image Steganalysis Based on Distortion Level Co-Occurrence Matrix

    Junjia Chen1, Wei Lu1,2,*, Yuileong Yeung1, Yingjie Xue1, Xianjin Liu1, Cong Lin1,3, Yue Zhang4

    CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 201-211, 2018, DOI:10.3970/cmc.2018.01781

    Abstract In recent years, binary image steganography has developed so rapidly that the research of binary image steganalysis becomes more important for information security. In most state-of-the-art binary image steganographic schemes, they always find out the flippable pixels to minimize the embedding distortions. For this reason, the stego images generated by the previous schemes maintain visual quality and it is hard for steganalyzer to capture the embedding trace in spacial domain. However, the distortion maps can be calculated for cover and stego images and the difference between them is significant. In this paper, a novel binary image steganalytic scheme is proposed,… More >

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