Digital Video Steganalysis Algorithm Based on Motion Estimation
SUN Yi-Feng1,2,LIU Fen-Lin1
Institute of Information Engineering,PLA Information Engineering University,Zhengzhou 450002 Institute of Electronic Technology,PLA Information Engineering University,Zhengzhou 450004
Abstract：A motion estimation based video steganalysis algorithm is proposed. The effect of information embedding on video motion estimation is investigated by the change of block mean square errors. The motion vectors are sensitive to information embedding, and the sensitivity increases with the decrease of the block size. The motion vector fields which reflect the time-variable characteristic of videos are used as the representation of video data in detecting stego-video. Firstly, a block size is given, and the motion vector fields are obtained by the minimum mean square error block matched motion estimation algorithm. Then the co-occurrence matrixes of three directional adjacent elements in the motions vector fields are calculated. The main diagonal elements and their neighbors of the co-occurrence matrixes are selected as the features. The support vector machine is adopted as the classifier. The experimental results show that the performance of the proposed algorithm is better compared with that of Budhia algorithm.
孙怡峰，刘粉林. 基于运动估计的视频隐写检测算法[J]. 模式识别与人工智能, 2010, 23(6): 759-771.
SUN Yi-Feng,LIU Fen-Lin. Digital Video Steganalysis Algorithm Based on Motion Estimation. , 2010, 23(6): 759-771.
[1] Cox I J, Kilian J, Leighton F T, et al. Secure Spread Spectrum Watermarking for Multimedia. IEEE Trans on Image Processing, 1997, 6(12): 1673-1687 [2] Marvel L M, Boncelet C G, Retter C T. Spread Spectrum Image Steganography. IEEE Trans on Image Processing, 1999, 8(8): 1075-1083 [3] Chen B, Wornell G W. Quantization Index Modulation: A Class of Provably Good Methods for Digital Watermarking and Information Embedding. IEEE Trans on Information Theory, 2001, 47(4):1423-1443 [4] Farid H. Detecting Hidden Messages Using Higher-Order Statistical Models // Proc of the IEEE International Conference on Image Processing. Rochester, USA, 2002: 905-908 [5] Goljan M, Fridrich J, Holotyak T. New Blind Steganalysis and Its Implications. Proc of SPIE, 2006, 6072: 1-13 [6] Harmsen J, Pearlman W. Steganalysis of Additive Noise Modelable Information Hiding. Proc of SPIE, 2003, 5020: 131-142 [7] Xuan Guorong, Shi Ya, Gao Jianjiong, et al. Steganalysis Based on Multiple Features Formed by Statistical Moments of Wavelet Characteristic Function // Proc of the Information Hiding Workshop. Barcelona, Spain, 2005: 262-277 [8] Wang Ying, Moulin P. Optimized Feature Extraction for Learning-Based Image Steganalysis. IEEE Trans on Information Forensics and Security, 2007, 2(1): 31-45 [9] Sullivan K, Madhow U, Chandrasekaran S, et al. Steganalysis for Markov Cover Data with Applications to Images. IEEE Trans on Information Forensics and Security, 2006, 1(2): 275-287 [10] Shi Y Q, Chen Chunhua, Chen Wen. A Markov Process Based Approach to Effective Attacking JPEG Steganography // Proc of the Information Hiding Workshop. Alexandria, USA, 2007: 249-264 [11] Liu Qingzhong, Sung A H, Chen Zhongxue, et al. Feature Mining and Pattern Classification for Steganalysis of LSB Matching Steganography in Grayscale Images. Pattern Recognition, 2008, 41(1): 56-66 [12] Pevn T, Bas P, Fridrich J. Steganalysis by Subtractive Pixel Adjacency Matrix // Proc of the 11th ACM Workshop on Multimedia and Security. Princeton, USA, 2009: 75-84 [13] Budhia U, Kundur D, Zourntos T. Digital Video Steganalysis Exploiting Statistical Visibility in the Temporal Domain. IEEE Trans on Information Forensics and Security, 2006, 1(4): 502-516 [14] Jainsky J S, Kundur D, Halverson D R. Towards Digital Video Steganalysis Using Asymptotic Memoryless Detection // Proc of the 9th ACM Workshop on Multimedia and Security. Dallas, USA, 2007: 161-167 [15] Zhang C, Su Y. Video Steganalysis Based on Aliasing Detection. Electronics Letters, 2008, 44(13): 801-803 [16] Pankajakshan V, Ho A T S. Improving Video Steganalysis Using Temporal Correlation // Proc of the 3rd IEEE International Conference on Intelligent Information Hiding and Multimedia Signal Processing. Kaohsiung, USA, 2007: 287-290 [17] Liu Bin, Liu Fenlin, Yang Chunfang. Video Steganalysis Scheme Based on Inter-Frame Collusion. Journal on Communications, 2009, 30(4): 41-49 (in Chinese) (刘 镔,刘粉林,杨春芳.基于帧间共谋的视频隐写分析.通信学报, 2009, 30(4): 41-49) [18] Su Yuting, Wang Lili, Zhang Chuntian. New Video Steganalysis Algorithm for MSU Stego Video. Journal of Southeast University: Natural Science Edition, 2007, 37(Z1): 164-167 (in Chinese) (苏育挺,王莉莉,张春田.一种新型视频信息隐藏分析算法.东南大学学报:自然科学版, 2007, 37(Z1): 164-167) [19] Su Yuting, Zhang Chengqian, Wang Lili, et al. A New Video Steganalysis Based on Mode Detection // Proc of the IEEE International Conference on Audio, Language and Image Processing. Shanghai, China, 2008: 1507-1510 [20] Liu Qingzhong, Sung A H, Qiao Mengyu. Video Steganalysis Based on the Expanded Markov and Joint Distribution on the Transform Domains Detecting MSU StegoVideo// Proc of the 7th International Conference on Machine Learning and Application. San Diego, USA, 2008: 671-674 [21] Kancherla K, Mukkamala S. Video Steganalysis Using Spatial and Temporal Redundancies // Proc of the IEEE International Conference on High Performance Computing Simulation. Leipzig, Germany, 2009: 200-207 [22] Filler T, Ker A D, Fridrich J. The Square Root Law of Steganographic Capacity for Markov Covers. Proc of SPIE, 2009, 7254: 1-11 [23] Tekalp A M. Digital Video Processing. Upper Saddle River, USA: Prentice Hall Press, 1995 [24] Richard O D, Peter E H, David G S. Pattern Classification. 2nd Edition. Hoboken, USA: Wiley-Interscience, 2000
2010, Vol. 23 
