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Detection of motion vector based video steganography

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Abstract

In this paper, a new steganalysis technique is proposed to detect the motion vector based steganography for the compressed videos. The proposed scheme explores the flickering effect, the changes in the prediction error and statistical anomalies in the motion vectors due to embedding to detect the presence of steganographic messages. The experimental results show that the proposed method effectively detects the data embedded in motion vector based steganographic techniques more accurately than the already existing schemes.

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References

  1. Aly HA (2011) Data hiding in motion vectors of compressed video based on their associated prediction error. Information forensics and security. IEEE Trans 6(1):14–18. doi:10.1109/TIFS.2010.2090520

    MathSciNet  Google Scholar 

  2. Avcibas I, Memon N, Sankur B (2003) Steganalysis using image quality metrics. Image Process IEEE Trans 12(2):221–229. doi:10.1109/TIP.2002.807363

    Article  MathSciNet  Google Scholar 

  3. Avcibas I, Nasir M, Sankur B (2001) Steganalysis based on image quality metrics. In: Multimedia signal processing. IEEE fourth workshop:517–522. doi:10.1109/MMSP.2001.962785

  4. Budhia U, Kundur D, Zourntos T (2006) Digital video steganalysis exploiting statistical visibility in the temporal domain. Inf Forensics Secur IEEE Trans 1(4):502–516. doi:10.1109/TIFS.2006.885020

    Article  Google Scholar 

  5. Cao Y, Zhao X, Feng D, Sheng R (2011) Video steganography with perturbed motion estimation. In: Proceedings of the 13th international conference on information hiding IH’11. Springer, Berlin, Heidelberg, pp 193–207. http://dl.acm.org/citation.cfm?id=2042445.2042463

    Google Scholar 

  6. Chebbo S, Durieux P, Pesquet-Popescu B (2010) Objective evaluation of compressed video’s temporal flickering. In: Image processing theory tools and applications (IPTA). 2nd Int conf:177–180. doi:10.1109/IPTA.2010.5586728

  7. Chen B, Wornell GW (2001) Quantization index modulation methods for digital watermarking and information embedding of multimedia. J VLSI Signal Process Syst 27(1/2):7–33. doi:10.1023/A:1008107127819

    Article  MATH  Google Scholar 

  8. Chen C, Shi YQ, Chen W, Xuan G (2006) Statistical moments based universal steganalysis using jpeg 2-d array and 2-d characteristic function. IEEE Int Conf Image Process:105–108. doi:10.1109/ICIP.2006.312383

  9. Dumitrescu S, Wu X, Wang Z (2003) Detection of lsb steganography via sample pair analysis. Signal Process IEEE Trans 51(7):1995–2007

    Article  Google Scholar 

  10. Fang D-Y, Chang L-W (2006) Data hiding for digital video with phase of motion vector. In: Circuits and systems, ISCAS. Proc IEEE Int Symp:4. doi:10.1109/ISCAS.2006.1692862

  11. Fisher RA (1936) The use of multiple measurements in taxonomic problems. Ann Eugenics 7(7):179–188

    Article  Google Scholar 

  12. Fridrich J (2005) Feature-based steganalysis for jpeg images and its implications for future design of steganographic schemes. In: Information hiding lecture notes in computer science, vol 3200. Springer, Berlin Heidelberg, pp 67–81. doi:10.1007/978-3-540-30114-1_6

    Google Scholar 

  13. He X, Luo Z (2008) A novel steganographic algorithm based on the motion vector phase. Comput Sci Softw Eng Int Conf 3:822–825. doi:10.1109/CSSE.2008.359

    Google Scholar 

  14. Huang F, Li B, Huang J (2007) Attack lsb matching steganography by counting alteration rate of the number of neighbourhood gray levels. IEEE Int Conf image Process ICIP 1:I401–I404. doi:10.1109/ICIP.2007.4378976

    Google Scholar 

  15. Jainsky JS, Kundur D, Halverson DR (2007) Towards digital video steganalysis using asymptotic memoryless detection. In: Proceedings of the 9th workshop on multimedia & security MM&Sec ’07. ACM, New York, USA, pp 161–168. doi:10.1145/1288869.1288891

    Google Scholar 

  16. Jue W, Min-qing Z, Juan-li S (2011) Video steganography using motion vector components. In: Communication Software and Networks (ICCSN). IEEE Int Conf:500–503. doi:10.1109/ICCSN.2011.6013642

  17. Ker AD (2005) Steganalysis of lsb matching in grayscale images. Signal Processing Letters, IEEE 12(6):441–444. doi:10.1109/LSP.2005.847889

    Article  Google Scholar 

  18. Marvel LM, Boncelet CGJ, Retter C (1999) Spread spectrum image steganography. Image Process IEEE Trans 8(8):1075–1083. doi:10.1109/83.777088

    Article  Google Scholar 

  19. Pankajakshan V, Ho A (2007) Improving video steganalysis using temporal correlation. Third Int Conf 1:287–290. doi:10.1109/IIHMSP.2007.4457546

    Google Scholar 

  20. Sharp T Hide 2.1. 2001. http://www.sharpthoughts.org

  21. Solanki K, Sarkar A, Manjunath BS (2007) Yass: yet another steganographic scheme that resists blind steganalysis. In: 9th int. workshop on info. hiding

  22. Tasdemir K, Kurugollu F, Sezer S (2013) Video steganalysis of lsb based motion vector steganography. In: Visual information processing (EUVIP), 2013 4th european workshop on pp. 260– 264

  23. Wang K, Han J, Wang H (2013) Digital video steganalysis by subtractive prediction error adjacency matrix. Multimedia Tools Appl:1–18. doi:10.1007/s11042-013-1373-4

  24. Wang P, Zheng Z, Ying J (2008) A novel video watermark technique in motion vectors. In: Audio, language and image processing, 2008. ICALIP 2008. Int Conf:1555–1559

  25. Westfeld A, Pfitzmann A (2000) Attacks on steganographic systems. In: Proceedings of the third international workshop on information hiding, IH ’99, Springer, London, UK. http://dl.acm.org/citation.cfm?id=647596.731699

  26. Xu C, Ping X, Zhang T (2006) Steganography in compressed video stream. In: Innovative computing, information and control, 2006. ICICIC ’06. First Int Conf 1:269–272. doi:10.1109/ICICIC.2006.158

    Google Scholar 

  27. Zhang C, Su Y, Zhang C (2008) A new video steganalysis algorithm against motion vector steganography. In: Wireless communications, networking and mobile computing, WiCOM ’08. Int Conf:1–4. doi:10.1109/WiCom.2008.781

  28. Zhang J, Li J, Zhang L (2001) Video watermark technique in motion vector. In: Computer graphics and image processing. In: Proceedings of XIV Brazilian symposium on, pp. 179–182

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Authors and Affiliations

  1. Department of Computer Science and Engineering, IIT Guwahati, Guwahati, 781039, India

    Arijit Sur, Sista Venkat Madhav Krishna, Nilkanta Sahu & Shuvendu Rana

Authors
  1. Arijit Sur
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  2. Sista Venkat Madhav Krishna
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  3. Nilkanta Sahu
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  4. Shuvendu Rana
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Correspondence to Nilkanta Sahu.

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Sur, A., Madhav Krishna, S.V., Sahu, N. et al. Detection of motion vector based video steganography. Multimed Tools Appl 74, 10479–10494 (2015). https://doi.org/10.1007/s11042-014-2181-1

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  • DOI: https://doi.org/10.1007/s11042-014-2181-1

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