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A Video Steganalysis Algorithm for H.264/AVC Based on the Markov Features

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9226))

Abstract

A new steganalysis algorithm based on the features of the original domain was proposed combining spatial correlation with temporal correlation among video frames. First, divide video frames into a new kind of special frame structure of P0-I-P1, calculate the luminance component for every frame of the macroblocks. And then we use the Eulerian-distance of vectors to express the correlation between macroblocks to get the most similar macroblock of adjacent frames. Thus, we combine the co-occurrence matrix model with Markov model into the P0-I and I-P1 frame type. We try to determine whether any data hiding is embedded in the video according to the changes of correlation between video frames. The experimental results show that the algorithm proposed in this paper has a high detection probability, and it calls the promising result and deserves further studies.

Foundation Item: The National Natural Science Foundation of China (61272407).

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References

  1. XU, C.Y.: Research on video steganography and video steganalysis. The PLA Information Engineering University (2009)

    Google Scholar 

  2. Xu, C.Y., Ping, X.J.: Video steganalysis based on spatial-temporal correlation. J. Image Graph. 1006–8961, 1331–1337 (2010)

    Google Scholar 

  3. Liu, B., Liu, F.L., Yang, C.F.: Video steganalysis scheme based on inter-frame collusion. J. Commun. 1000-436X, 41–49 (2009)

    Google Scholar 

  4. Sun, Y.F., LIU, F.L.: Digital video steganalysis algorithm based on motion estimation. Pattern Recogn. Artif. Intell. 1003–6059, 759–765 (2010)

    Google Scholar 

  5. Deng, Q.L., Lin, J.J.: Image steganalysis based on co-ocurrence matrix. Microcomput. Inf. 1008–0570, 6–8 (2009)

    Google Scholar 

  6. Burges, C.: A tutorial on support vector machines for pattern recognition. Data Min. Knowl. Disc. 2, 121–167 (1998)

    Article  Google Scholar 

  7. Tian, L.H., Zheng, N.N., Xue, J.R., et al.: A CAVLC-based blind watermarking method for H.264/AVC compressed video. In: Asia-Pacific Services Computing Conference. APSCC, Yilan, Taiwan, pp. 1295–1299 (2008)

    Google Scholar 

  8. Wang, B., Feng, J.C.: A chaos-based steganography algorithm for H.264 standard video sequences. In: International Conference on Communications, Circuits and Systems, ICCCAS 2008, Xiamen, China, pp. 750–753 (2008)

    Google Scholar 

  9. Su, P., Li, M., Chen, I.: A content-adaptive digital watermarking scheme in H.264/AVC compressed videos. In: International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP, Harbin, China, pp. 849–852 (2008)

    Google Scholar 

  10. Bhattacharya, S., Chattopadhyay, T., Pal, A.: A survey on different video watermarking techniques and comparative analysis with reference to H.264/AVC. In: 2006 ISCE International Symposium on Consumer Electronics, Samos Island, Greece, pp. 1–6 (2006)

    Google Scholar 

  11. Ma, X.J., Li, Zh.T., Tu, H., Zhang, B.C.: A data hiding algorithm for H.264/AVC video streams without intra-frame distortion drift. IEEE Trans. Circ. Syst. Video Technol. 20(4), 1320–1330 (2010)

    Article  Google Scholar 

  12. Fridrich, J., Goljan, M., Hogea, D.: Steganalysis of JPEG images breaking the F5 algorithm. In: Petitcolas, F.A.P. (ed.) IH 2002. LNCS, vol. 2578, pp. 310–323. Springer, Heidelberg (2002)

    Google Scholar 

  13. Fridrich, J., Goljan, M., Hogea, D.: Attacking the outguess. In: Proceeding of ACM Workshop on Multimedia and Security, pp. 967–982 (2002)

    Google Scholar 

  14. Wang, M., Fan, K., Yue, B., et al.: A content protection scheme for H.264-based video sequence. In: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2007, Qingdao, China, pp. 388–393 (2007)

    Google Scholar 

  15. Hartung, F., Girod, B.: Digital watermarking of MPEG-2 coded video in the bitstream domain. In: IEEE International Conference on the Acoustics, Speech, and Signal Processing, ICASSP, Munich, Germany, pp. 2621–2624 (1997)

    Google Scholar 

  16. Lu, C.S., Chung, P.C., Chen, C.F.: Unsupervised texture segmentation via wavelet transform. Pattern Recogn. 30(0031–3203), 729–742 (1997)

    Article  Google Scholar 

  17. Guo, D.J., Song, Z.C.: A study on texture image classifying based on gray-level co-ocurrence matrix. For. Mach. Woodwork. Equip. 1001–4462, 21–23 (2005)

    MATH  Google Scholar 

  18. Cao, J.N., Li, D.R., Guan, Z.Q.: Study on approach of detection for video image basedon decomposable markov network. Acta Optica Sinica 0253–2239, 312–318 (2005)

    Google Scholar 

  19. WEI, S.Y., NING, C., GAO, Y.X.: Biomimetic gait recognition based on motion contours wavelets analysis and mutual information. In: 2010 3rd International Congress on Image and Signal Processing, 1, pp. 404–408. IEEE, Piscataway (2010)

    Google Scholar 

  20. Rana, V., Mishra, R., Bora, P.K., Kashyap, S.: Novel scheme of video steganalysis for detecting antipodal watermarks. In: Proceedings IEEE Region 10 Conference-TENCON, pp. 1–5 (2008)

    Google Scholar 

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Correspondence to ZhiTang Li .

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Da, T., Li, Z., Feng, B. (2015). A Video Steganalysis Algorithm for H.264/AVC Based on the Markov Features. In: Huang, DS., Jo, KH., Hussain, A. (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in Computer Science(), vol 9226. Springer, Cham. https://doi.org/10.1007/978-3-319-22186-1_5

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  • DOI: https://doi.org/10.1007/978-3-319-22186-1_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22185-4

  • Online ISBN: 978-3-319-22186-1

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