KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
권호 표지
DOI QR코드

DOI QR Code

Forensics Aided Steganalysis of Heterogeneous Bitmap Images with Different Compression History

  • Hou, Xiaodan (Zhengzhou Information Science and Technology Institute) ;
  • Zhang, Tao (Zhengzhou Information Science and Technology Institute) ;
  • Xiong, Gang (Zhengzhou Information Science and Technology Institute) ;
  • Wan, Baoji (Zhengzhou Information Science and Technology Institute)
  • Received : 2012.06.04
  • Accepted : 2012.08.16
  • Published : 2012.08.25
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, two practical forensics aided steganalyzers (FA-steganalyzer) for heterogeneous bitmap images are constructed, which can properly handle steganalysis problems for mixed image sources consisting of raw uncompressed images and JPEG decompressed images with different quality factors. The first FA-steganalyzer consists of a JPEG decompressed image identifier followed by two corresponding steganalyzers, one of which is used to deal with uncompressed images and the other is used for mixed JPEG decompressed images with different quality factors. In the second FA-steganalyzer scheme, we further estimate the quality factors for JPEG decompressed images, and then steganalyzers trained on the corresponding quality factors are used. Extensive experimental results show that the proposed two FA-steganalyzers outperform the existing steganalyzer that is trained on a mixed dataset. Additionally, in our proposed FA-steganalyzer scheme, we can select the steganalysis methods specially designed for raw uncompressed images and JPEG decompressed images respectively, which can achieve much more reliable detection accuracy than adopting the identical steganalysis method regardless of the type of cover source.

Keywords

References

  1. J. Fridrich, M. Goljan and D. Hogea, "Steganalysis of JPEG images: Breaking the F5 algorithm," in Proc. of 5th International Workshop on Information Hiding, pp. 310-323, Oct. 2002.
  2. G. Cancelli, G. Doerr, I. Cox and M. Barni, "A comparative study of ${\pm}1$ steganalyzers," in Proc. of IEEE International Workshop on Multimedia Signal Processing, pp. 791-796, Oct. 2008.
  3. T. Pevny, P. Bas and J. Fridrich, "Steganalysis by subtractive pixel adjacency matrix," IEEE Transaction on Information Forensics and Security, vol. 5, no. 2, pp. 215-224, Mar. 2010. https://doi.org/10.1109/TIFS.2010.2045842
  4. T. Pevny and J. Fridrich, "Determining the stego algorithm for JPEG images," Special Issue of IEE Processing Information Security, vol. 153, no. 3, pp. 77-86, Sep. 2006. https://doi.org/10.1049/ip-ifs:20055147
  5. T. Pevny and J. Fridrich, "Multiclass detector of current steganographic methods for JPEG format," IEEE Transaction on Information Forensics and Security, vol. 3, no. 4, pp. 635-650, Dec. 2008. https://doi.org/10.1109/TIFS.2008.2002936
  6. M. Barni, G. Cancelli and A. Esposito, "Forensics aided steganalysis of heterogeneous images," in Proc. of IEEE Conf. on Acoustic Speech, Signal Processing, pp. 1690-1693, Mar. 2010.
  7. H. Amirkhani and M. Rahmati, "New framework for using image contents in blind steganalysis systems," Journal of Electronic Imaging, vol. 20, no. 1, pp. 1-14, Mar. 2011.
  8. W. Luo, F. Huang and J. Huang, "JPEG error analysis and its applications to digital image forensics," IEEE Trans. on Information Forensics and Security, vol. 5, no. 3, pp. 480-491, Sep. 2010. https://doi.org/10.1109/TIFS.2010.2051426
  9. T. Sharp, "An Implementation of key-based digital signal steganography," in Proc. of 4th International Workshop on Information Hiding, pp. 13-26, Apr. 2001.
  10. G. Doerr, Image Database for Steganalysis Studies [Online]. Available: http://www.cs.ucl.ac.uk/ staff/I.Cox/Content/Downloads.html.
  11. E. Zheng, X. Ping and T. Zhang, "Local linear transform and new features of histogram characteristic functions for steganalysis of least significant bit matching steganography," KSII Transaction on Internet and Information System, vol. 5, no. 4, pp. 840-855, Apr. 2011.
  12. K. Cai, X. Li and T. Zeng, "Reliable histogram features for detecting LSB matching," in Proc. of IEEE Conf. on Image Processing, pp. 1761-1764, Sep. 2010.
  13. J. Zhang and D. Zhang, "Detection of LSB matching steganography in decompressed images," IEEE Signal Processing Letters, vol. 17, no. 2, pp. 141-144, Feb. 2010. https://doi.org/10.1109/LSP.2009.2035379
  14. X. Li, T. Zhang, Y. Zhang, W. Li and K. Li, "A novel blind detector for additive noise steganography in JPEG decompressed images," Multimedia Tools and Applications, published online, May. 2012.
  15. M. Goljan, J. Fridrich and T. Holotyak, "New blind steganalysis and its implications," in Proc. of SPIE Electronic Imaging, Security, Steganography, and Watermarking of Multimedia Contents VIII, pp. 1-13, Jan. 2006.
  16. B. Li, J. Huang and Y. Q. Shi, "Textural features based universal steganalysis," in Proc. of SPIE Security, Forensics, Steganography and Watermarking of Multimedia, pp. 1201-1212, Jan. 2008.
  17. W. Luo, Y. Wang and J. Huang, "Security analysis on spatial ${\pm}1$ steganography for JPEG decompressed images," IEEE Signal Processing Letters, vol. 18, no. 1, pp. 39-42, Jan. 2011. https://doi.org/10.1109/LSP.2010.2091127

Cited by

  1. Detection for Operation Chain: Histogram Equalization and Dither-like Operation vol.9, pp.9, 2012, https://doi.org/10.3837/tiis.2015.09.026
  2. Steganalysis aided by fragile detection of image manipulations vol.78, pp.16, 2012, https://doi.org/10.1007/s11042-019-7654-9