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基于修改概率转换和非加性嵌入失真的视频隐写方法

李林聪 姚远志 张晓雅 张卫明 俞能海

李林聪, 姚远志, 张晓雅, 张卫明, 俞能海. 基于修改概率转换和非加性嵌入失真的视频隐写方法[J]. 电子与信息学报, 2020, 42(10): 2357-2364. doi: 10.11999/JEIT200001
引用本文: 李林聪, 姚远志, 张晓雅, 张卫明, 俞能海. 基于修改概率转换和非加性嵌入失真的视频隐写方法[J]. 电子与信息学报, 2020, 42(10): 2357-2364. doi: 10.11999/JEIT200001
Lincong LI, Yuanzhi YAO, Xiaoya ZHANG, Weiming ZHANG, Nenghai YU. Video Steganography Based on Modification Probability Transformation and Non-additive Embedding Distortion[J]. Journal of Electronics & Information Technology, 2020, 42(10): 2357-2364. doi: 10.11999/JEIT200001
Citation: Lincong LI, Yuanzhi YAO, Xiaoya ZHANG, Weiming ZHANG, Nenghai YU. Video Steganography Based on Modification Probability Transformation and Non-additive Embedding Distortion[J]. Journal of Electronics & Information Technology, 2020, 42(10): 2357-2364. doi: 10.11999/JEIT200001

基于修改概率转换和非加性嵌入失真的视频隐写方法

doi: 10.11999/JEIT200001
基金项目: 国家自然科学基金(61802357, U1636201),国家重点研发计划项目(2018YFB0804102),中央高校基本科研业务费专项资金(WK3480000009)
详细信息
    作者简介:

    李林聪:男,1996年生,博士生,研究方向为信息隐藏、深度学习

    姚远志:男,1989年生,副研究员,研究方向为信息隐藏、视频编码

    张晓雅:女,1998年生,硕士生,研究方向为信息隐藏、计算机视觉

    张卫明:男,1976年生,教授,博士生导师,研究方向为信息隐藏、多媒体安全、隐私保护

    俞能海:男,1964年生,教授,博士生导师,研究方向为图像视频处理与分析、计算机视觉与模式识别、信息隐藏与媒体内容安全、信息检索与数据挖掘

    通讯作者:

    姚远志 yaoyz@ustc.edu.cn

  • 中图分类号: TN918

Video Steganography Based on Modification Probability Transformation and Non-additive Embedding Distortion

Funds: The National Natural Science Foundation of China (61802357, U1636201), The National Key Research and Development Program of China (2018YFB0804102), The Fundamental Research Funds for the Central Universities (WK3480000009)
  • 摘要: 近年来,基于运动矢量的视频隐写引起了信息隐藏领域研究者的广泛关注。许多视频隐写方法通过合理地对运动矢量定义加性嵌入失真函数获得了良好的性能,然而这些方法忽略了载体元素之间的相互嵌入影响。该文提出的利用非加性嵌入失真的视频隐写方法为运动矢量设计了可以反映相互嵌入影响的联合嵌入失真,并通过分解联合失真实现修改概率的转换,从而动态、合理地在运动矢量的水平分量和垂直分量分配秘密消息。实验结果表明,与使用加性嵌入失真方法相比,该方法能获得更好的安全性和率失真性能。
  • 图  1  本文和文献[9]的方法的失真函数选定不同参数时抵抗隐写分析方法S1和S2的性能

    图  2  5种隐写方法抵抗3种隐写分析方法的性能

    图  3  5种隐写方法抵抗3种隐写分析方法的综合性能

    表  1  5种嵌入率下5种隐写方法抵抗3种隐写分析方法的最小平均误分类概率(%)

    嵌入率(bpmv)文献[4]方法文献[5]方法文献[6]方法文献[9]方法本文方法
    S1S2S3S1S2S3S1S2S3S1S2S3S1S2S3
    0.146.5437.1917.5646.2916.0216.1240.3640.9517.2645.5541.1021.0248.7142.1421.51
    0.241.6926.0111.8239.868.3611.7732.0037.2913.8542.6837.7814.9446.5441.3016.96
    0.337.2923.549.5034.086.089.7426.2133.8812.4138.3834.0312.7142.9841.2015.68
    0.434.5217.115.9326.164.556.7317.1628.049.7934.3225.8210.0440.0636.8415.18
    0.531.7513.954.9522.263.075.6412.3124.137.9631.9521.177.8137.2434.8212.81
    下载: 导出CSV

    表  2  嵌入率为0.5bpmv时5种隐写方法得到的载密视频亮度分量的平均PSNR (dB)

    视频序列载体视频文献[4]方法文献[5]方法文献[6]方法文献[9]方法本文方法
    Bus34.42534.18534.23534.26534.27034.295
    City34.67634.41234.43234.46434.47234.494
    Coastguard34.41034.21234.23434.25634.26234.286
    Crew36.94836.79836.79036.81636.81436.844
    Flower34.52034.27034.36234.44034.42534.460
    Football35.93835.84235.84835.83835.84535.860
    Foreman36.08035.81435.79435.86835.87635.900
    Harbour34.04633.86433.85433.89833.89233.924
    Ice39.55839.28239.27039.38239.38039.405
    Mobile33.61633.45433.43033.50633.49433.524
    Paris33.51835.37535.24335.43635.40135.450
    Soccer35.66435.49635.50435.50435.51835.548
    Stefan35.34035.07035.03035.21035.19035.240
    Tempete34.52034.35834.32034.38834.39234.418
    Waterfall34.68834.25034.33834.36034.38834.405
    下载: 导出CSV

    表  3  嵌入率为0.5bpmv时5种隐写方法得到载密视频的平均比特率扩张(%)

    视频序列文献[4]方法文献[5]方法文献[6]方法文献[9]方法本文方法
    Bus12.8114.033.485.773.39
    City22.9220.479.0210.347.01
    Coastguard6.789.723.924.642.94
    Crew3.994.953.103.151.95
    Flower14.8715.262.935.141.74
    Football2.153.271.842.171.23
    Foreman11.9218.455.976.524.63
    Harbour6.977.343.154.132.72
    Ice16.0518.034.716.534.17
    Mobile9.9513.103.495.643.00
    Paris10.4419.152.516.592.46
    Soccer5.347.783.984.572.98
    Stefan13.9514.893.635.132.39
    Tempete8.8912.933.844.392.71
    Waterfall18.7820.209.118.736.70
    下载: 导出CSV

    表  4  文献[9]方法和本文方法在嵌入消息和编码视频步骤的平均执行时间(s)

    隐写方法嵌入消息编码视频总计
    文献[9]方法3.3992.2695.65
    本文方法3.3892.6696.04
    下载: 导出CSV
  • HUSSAIN M, WAHAB A W A, IDRIS Y I B, et al. Image steganography in spatial domain: A survey[J]. Signal Processing: Image Communication, 2018, 65: 46–66. doi: 10.1016/j.image.2018.03.012
    吴志军, 李常亮, 李荣. 基于随机位置选择和矩阵编码的语音信息隐藏方法[J]. 电子与信息学报, 2020, 42(2): 355–363. doi: 10.11999/JEIT181163

    WU Zhijun, LI Changliang, and LI Rong. Speech information hiding method based on random position selection and matrix coding[J]. Journal of Electronics &Information Technology, 2020, 42(2): 355–363. doi: 10.11999/JEIT181163
    LIU Yunxia, LIU Shuyang, WANG Yonghao, et al. Video steganography: A review[J]. Neurocomputing, 2019, 335: 238–250. doi: 10.1016/j.neucom.2018.09.091
    XU Changyong, PING Xijian, and ZHANG Tao. Steganography in compressed video stream[C]. The 1st International Conference on Innovative Computing, Information and Control-Volume I (ICICIC'06), Beijing, China, 2006: 269–272. doi: 10.1109/ICICIC.2006.158.
    ALY H A. Data hiding in motion vectors of compressed video based on their associated prediction error[J]. IEEE Transactions on Information Forensics and Security, 2011, 6(1): 14–18. doi: 10.1109/TIFS.2010.2090520
    CAO Yun, ZHAO Xianfeng, FENG Dengguo, et al. Video steganography with perturbed motion estimation[C]. The 13th International Conference on Information Hiding, Prague, Czech Republic, 2011: 193–207. doi: 10.1007/978-3-642-24178-9_14.
    FRIDRICH J, GOLJAN M, LISONEK P, et al. Writing on wet paper[J]. IEEE Transactions on Signal Processing, 2005, 53(10): 3923–3935. doi: 10.1109/TSP.2005.855393
    FILLER T, JUDAS J, and FRIDRICH J. Minimizing additive distortion in steganography using syndrome-trellis codes[J]. IEEE Transactions on Information Forensics and Security, 2011, 6(3): 920–935. doi: 10.1109/TIFS.2011.2134094
    YAO Yuanzhi, ZHANG Weiming, YU Nenghai, et al. Defining embedding distortion for motion vector-based video steganography[J]. Multimedia Tools and Applications, 2015, 74(24): 11163–11186. doi: 10.1007/s11042-014-2223-8
    ZHANG Hong, CAO Yun, and ZHAO Xianfeng. Motion vector-based video steganography with preserved local optimality[J]. Multimedia Tools and Applications, 2016, 75(21): 13503–13519. doi: 10.1007/s11042-015-2743-x
    ZHU Baolin and NI Jiangqun. Uniform embedding for efficient steganography of H. 264 video[C]. The 25th IEEE International Conference on Image Processing (ICIP), Athens, Greece, 2018: 1678–1682. doi: 10.1109/ICIP.2018.8451214.
    SU Yuting, ZHANG Chengqian, and ZHANG Chuntian. A video steganalytic algorithm against motion-vector-based steganography[J]. Signal Processing, 2011, 91(8): 1901–1909. doi: 10.1016/j.sigpro.2011.02.012
    CAO Yun, ZHAO Xianfeng, and FENG Dengguo. Video steganalysis exploiting motion vector reversion-based features[J]. IEEE Signal Processing Letters, 2012, 19(1): 35–38. doi: 10.1109/LSP.2011.2176116
    WANG Keren, ZHAO Hong, and WANG Hongxia. Video steganalysis against motion vector-based steganography by adding or subtracting one motion vector value[J]. IEEE Transactions on Information Forensics and Security, 2014, 9(5): 741–751. doi: 10.1109/TIFS.2014.2308633
    ZHANG Hong, CAO Yun, and ZHAO Xianfeng. A steganalytic approach to detect motion vector modification using near-perfect estimation for local optimality[J]. IEEE Transactions on Information Forensics and Security, 2017, 12(2): 465–478. doi: 10.1109/TIFS.2016.2623587
    LI Bin, WANG Ming, LI Xiaolong, et al. A strategy of clustering modification directions in spatial image steganography[J]. IEEE Transactions on Information Forensics and Security, 2015, 10(9): 1905–1917. doi: 10.1109/TIFS.2015.2434600
    汤光明, 姜明明, 孙艺. 失真代价动态更新的自适应彩色图像隐写算法[J]. 电子与信息学报, 2019, 41(3): 656–665. doi: 10.11999/JEIT180388

    TANG Guangming, JIANG Mingming, and SUN Yi. Adaptive color image steganography based on dynamic distortion modification[J]. Journal of Electronics &Information Technology, 2019, 41(3): 656–665. doi: 10.11999/JEIT180388
    LI Weixiang, ZHANG Weiming, CHEN Kejiang, et al. Defining joint distortion for JPEG steganography[C]. The 6th ACM Workshop on Information Hiding and Multimedia Security, Innsbruck, Austria, 2018: 5–16. doi: 10.1145/3206004.3206008.
    ZHANG Weiming, ZHANG Zhuo, ZHANG Lili, et al. Decomposing joint distortion for adaptive steganography[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2017, 27(10): 2274–2280. doi: 10.1109/TCSVT.2016.2587388
    周洋, 吴佳忆, 陆宇, 等. 面向三维高效视频编码的深度图错误隐藏[J]. 电子与信息学报, 2019, 41(11): 2760–2767. doi: 10.11999/JEIT180926

    ZHOU Yang, WU Jiayi, LU Yu, et al. Depth map error concealment for 3D high efficiency video coding[J]. Journal of Electronics &Information Technology, 2019, 41(11): 2760–2767. doi: 10.11999/JEIT180926
    FILLER T and FRIDRICH J. Gibbs construction in steganography[J]. IEEE Transactions on Information Forensics and Security, 2010, 5(4): 705–720. doi: 10.1109/TIFS.2010.2077629
    KODOVSKY J, FRIDRICH J, and HOLUB V. Ensemble classifiers for steganalysis of digital media[J]. IEEE Transactions on Information Forensics and Security, 2012, 7(2): 432–444. doi: 10.1109/TIFS.2011.2175919
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出版历程
  • 收稿日期:  2020-01-02
  • 修回日期:  2020-08-04
  • 网络出版日期:  2020-08-12
  • 刊出日期:  2020-10-13

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