Active steganalysis based on pixels classification in the image

被引:0
|
作者
Liu, Jing [1 ]
Tang, Guang-Ming [1 ]
机构
[1] Institute of Electronic Technology, Information Engineering University, Zhengzhou 450004, China
关键词
Active steganalysis - Hidden information - Least significant bits - LSB replacement steganography - Physical significance - Pixel classification - Steganalysis - Stego key;
D O I
10.3724/SP.J.1146.2011.01422
中图分类号
学科分类号
摘要
The research on steganalysis has mainly focused on hidden information detection, and there are few methods about active steganalysis. From the view of hidden information detection, the pixels are classified into different kinds. Based on the analysis of the effects on the frequencies of different kinds of pixels by message embedding and Least Significant Bit (LSB) plane flipping, an active steganalysis approach is proposed to recover the stego key of LSB replacement steganography in spatial domain of images. This method has remarkable physical significance and can be implemented conveniently. Experimental results show that this method can recover the stego key successfully in certain range of embedding ratio.
引用
收藏
页码:1928 / 1933
相关论文
共 50 条
  • [41] Classification accuracy improvement and delineation of mixed pixels using hierarchical image classification
    Ediriwickrema, J
    IGARSS '96 - 1996 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM: REMOTE SENSING FOR A SUSTAINABLE FUTURE, VOLS I - IV, 1996, : 793 - 795
  • [42] Large Scale Image Steganalysis Based on MapReduce
    Sun, Zhanquan
    Huang, Huifen
    Li, Feng
    ADVANCES IN NEURAL NETWORKS - ISNN 2016, 2016, 9719 : 3 - 11
  • [43] Image Steganalysis Based on Wavelet Packet Decomposition
    Yu, Lei
    PROCEEDINGS OF THE 2018 3RD INTERNATIONAL WORKSHOP ON MATERIALS ENGINEERING AND COMPUTER SCIENCES (IWMECS 2018), 2018, 78 : 363 - 366
  • [44] Experiments on Image Classification and Retrieval using Statistics on Pixels Position
    Pavaloi, Ioan
    Nita, Cristina Diana
    2017 INTERNATIONAL SYMPOSIUM ON SIGNALS, CIRCUITS AND SYSTEMS (ISSCS), 2017,
  • [45] A review on deep learning based image steganalysis
    Tang, Yong-he
    Jiang, Lie-hui
    He, Hong-qi
    Dong, Wei-yu
    PROCEEDINGS OF 2018 IEEE 3RD ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC 2018), 2018, : 1764 - 1770
  • [46] Image steganalysis based on attention augmented convolution
    Huang, Siyuan
    Zhang, Minqing
    Ke, Yan
    Bi, Xinliang
    Kong, Yongjun
    MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (14) : 19471 - 19490
  • [47] Image steganalysis based on the modularized residual network
    Guo J.
    He Y.
    Wei H.
    Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University, 2019, 46 (01): : 79 - 85
  • [48] An Image Steganalysis Algorithm based on Feature Importance
    Yu, Wenqiong
    2011 INTERNATIONAL CONFERENCE ON FUTURE COMPUTER SCIENCE AND APPLICATION (FCSA 2011), VOL 1, 2011, : 257 - 260
  • [49] Image steganalysis based on attention augmented convolution
    Siyuan Huang
    Minqing Zhang
    Yan Ke
    Xinliang Bi
    Yongjun Kong
    Multimedia Tools and Applications, 2022, 81 : 19471 - 19490
  • [50] WPD-based blind image steganalysis
    Institute of Information Engineering, PLA Information Engineering University, Zhengzhou 450002, China
    不详
    Tongxin Xuebao, 2008, 10 (173-182):