基于关联网络模型的H.264/AVC运动矢量调制信息隐藏检测方法

doi:10.3969/j.issn.0255-8297.2019.05.008

应用科学学报 ›› 2019, Vol. 37 ›› Issue (5): 663-672.doi: 10.3969/j.issn.0255-8297.2019.05.008

基于关联网络模型的H.264/AVC运动矢量调制信息隐藏检测方法

李松斌¹, 杨洁², 刘鹏¹, 王凌睿¹

1. 中国科学院声学研究所南海研究站, 海口 570105;
2. 浙江农林大学暨阳学院工程技术学院, 浙江诸暨 311800

收稿日期:2019-07-27 修回日期:2019-08-01 出版日期:2019-09-30 发布日期:2019-10-18
通信作者: 李松斌,研究员,研究方向:多媒体内容安全,E-mail:lisongbin@mail.ioa.ac.cn E-mail:lisongbin@mail.ioa.ac.cn
基金资助:
海南省重大科技计划项目（No.ZDKJ201807）；国家自然科学基金（No.U1636113）；海南自然科学基金（No.618QN309）；中国科学院声学研究所青年英才计划项目（No.QNYC201829，No.QNYC201747）；中国科学院声学研究所南海研究站资助科研基金（No.2018001）资助

Steganalysis of Motion Vector-Based Steganography in H.264/AVC by Correlation Network Model

LI Songbin¹, YANG Jie², LIU Peng¹, WANG Lingrui¹

1. Haikou Laboratory, Institute of Acoustics, Chinese Academy of Sciences, Haikou 570105, China;
2. College of Engineering and Technolog, Jiyang College of Zhejiang A & F University, Zhuji 311800, Zhejiang Province, China

Received:2019-07-27 Revised:2019-08-01 Online:2019-09-30 Published:2019-10-18

摘要/Abstract

摘要： H.264/AVC运动矢量信息隐藏方法具有较大的嵌入容量，同时对重建帧的视频质量引入的附加失真较小，是一种重要的H.264/AVC视频信息隐藏方法.针对该种信息隐藏方法提出了一种隐写分析方法.由于视频帧中物体的完整性和物体在帧间运动的连续性，H.264/AVC时域及空域中相邻编码宏块的运动矢量存在一定的相关性.据此，建立了用于运动矢量隐写分析的时空相邻宏块运动矢量关联网络模型.通过对关联网络进行剪枝得到强相关网络，并对强相关网络中顶点之间的相关性进行了量化表示，从而提取了用于隐写分析的特征向量，结合支持向量机（support vector machine，SVM）构建了隐写检测器.实验表明，与现有的隐写分析算法相比，该文方法具有更好的检测性能，检测准确率均超过90%.

关键词: H.264/AVC, 视频信息隐藏, 隐写分析, 运动矢量, 关联网络

Abstract: Motion vector modulated steganographic approach is an important type of information hiding method in H.264/AVC video streams, due to its large embedding capacity and low additional distortion induced in reconstructed video frames. In this paper, a novel video steganalysis algorithm is proposed for this type of information hiding method. Firstly, this paper designs a correlation network model to illustrate the correlation between temporal and spatial adjacent motion vectors. Secondly, we obtain a strong correlation network model by simplifying the original correlation network model through a pruning process, accordingly, the quantitative feature vectors of the strong model can be represented through quantifying the correlation of vertexes for steganalysis purpose. Finally, a steganographic detector based on the extracted feature vectors is built by using the support vector machine (SVM). Experiment results show that the proposed algorithm achieves a satisfying performance with the detection accuracy of more than 90%.

Key words: H.264/AVC, video information hiding, steganalysis, motion vector, correlation network

中图分类号:

P751.1

李松斌, 杨洁, 刘鹏, 王凌睿. 基于关联网络模型的H.264/AVC运动矢量调制信息隐藏检测方法[J]. 应用科学学报, 2019, 37(5): 663-672.

LI Songbin, YANG Jie, LIU Peng, WANG Lingrui. Steganalysis of Motion Vector-Based Steganography in H.264/AVC by Correlation Network Model[J]. Journal of Applied Sciences, 2019, 37(5): 663-672.

参考文献

[1] Jordan F, Kutter M, Ebrahimi T. Proposal of a watermarking technique for hiding/retrieving data in compressed and decompressed video. ISO/IEC document, JTCI/SC29/WG11, MPEG 97/M 2281, 1997.
[2] Dai Y J, Zhang L H, Yang Y X. A new method of MPEG video watermarking technology[C]//Proceedings of 2003 International Conference on Communication Technology, 2003:1845-1847.
[3] Zhang J, Maitre H, Li J G, et al. Embedding water-mark in MPEG video sequence[C]//IEEE Fourth Workshop on Multimedia Signal Processing. IEEE, 2001:535-540.
[4] Hao B, Zhao L Y, Zhong W D. A novel steganographic algorithm based on motion vector and matrix decoding[C]//IEEE 3rd International Conference on Communication Software and Networks, 2011:406-409.
[5] Kuo T Y, Lo Y C, Lin C I. Fragile video watermarking technique by motion field embedding with rate-distortion minimization[C]//International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2008:853-856.
[6] Guo Y, Pan F. Information hiding for H.264 in video stream switching application[C]//IEEE International Conference on Information Theory and Information Security, 2010:419-421.
[7] Mohaghegh N, Fatemi O. H.264 copyright protection with motion vector watermarking[C]//International Conference on Audio, Language and Image Processing, 2008:1384-1389.
[8] Xu C, Ping X, Zhang T. Steganography in compressed video stream[C]//Proceedings of 1st International Conference on Innovative Computing Information and Control, 2006:269-272.
[9] Aly H. 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.
[10] Cao Y, Zhao X F, Feng D G, et al. Video steganography with perturbed motion estimation[C]//Processing of 13th International Conference, 2011, 6958:193-207.
[11] Zhu J J, Wei L X, Yang X Y, et al. High capacity H.264 video steganographic algorithm based on motion offset[J]. Computer Engineering, 2011, 37(18):136-138.
[12] Zhu H, Wang R, Xu D. Information hiding algorithm for H.264 based on the motion estimation of quarter-pixel[C]//Proceedings of 2nd International Conference Future Computer and Communication, 2010, 1:423-427.
[13] Swaraja K, Latha Y M, Reddy V S K, et al. Video watermarking based on motion vectors of H.264[C]//Proceedings of 2011 Annual IEEE India Conference, 2011:1-4.
[14] Yao Y Z, Zhang W M, Yu N H, et al. Defining embedding distortion for motion vector-based video steganography[J]. Multimedia Tools and Applications, 2015, 74(24):11163-11186.
[15] 李松斌,王凌睿,刘鹏,等. 一种基于运动矢量空间编码的HEVC信息隐藏方法[J]. 计算机学报,2016, 39(7):1450-1463. Li S B, Wang L R, Liu P, et al. A HEVC information hiding approach based on motion vection space encoding[J]. Journal of Computers,2016, 39(7):1450-1463. (in Chinese)
[16] Zhang C, Su Y, Zhang C. Video steganalysis based on aliasing detection[J]. Electronics Letters, 2008, 44(13):801-803.
[17] Su Y, Zhang C, Zhang C. A video steganalytic algorithm against motion-vector-based steganography[J]. Signal Processing, 2011, 91(8):1901-1909.
[18] Cao Y, Zhao X, Feng D. Video steganalysis exploiting motion vector reversion-based features[J]. IEEE Signal Processing Letters, 2012, 19(1):35-38.
[19] Deng Y, Wu Y, Duan H, et al. Digital video steganalysis based on motion vector statistical characteristics[J]. Optik International Journal Light Electron Optics, 2013, 124:1705-1710.
[20] Wang K, Zhao H, Wang H. 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.
[21] Zhang H, Cao Y, Zhao X. 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.
[22] Elaheh S, Karim F, Mohsen S P. Entropy-based video steganalysis of motion vectors[J]. Entropy, 2018, 20(4):244-257.

基于关联网络模型的H.264/AVC运动矢量调制信息隐藏检测方法

Steganalysis of Motion Vector-Based Steganography in H.264/AVC by Correlation Network Model

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