Binary Image Steganographic Techniques Classification Based on Multi-class Steganalysis

1. Böhme, R., Westfeld, A.: Breaking cauchy model-based jpeg steganography with first order statistics. In: Samarati, P., Ryan, P.Y.A., Gollmann, D., Molva, R. (eds.) ESORICS 2004. LNCS, vol. 3193, pp. 125–140. Springer, Heidelberg (2004)

   Google Scholar 

2. Chang, C.-C., Lin, C.-J.: LIBSVM: a library for support vector machines (2001), Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm

3. Chang, C.-C., Tseng, C.-S., Lin, C.-C.: Hiding data in binary images. In: Deng, R.H., Bao, F., Pang, H., Zhou, J. (eds.) ISPEC 2005. LNCS, vol. 3439, pp. 338–349. Springer, Heidelberg (2005)

   Google Scholar 

4. Chiew, K.L., Pieprzyk, J.: A countermeasure for binary image steganography. In: International Conference on Availability, Reliability and Security (2010)

   Google Scholar 

5. Cortes, C., Vapnik, V.: Support-vector networks. Machine Learning 20(3), 273–297 (1995)

   MATH  Google Scholar 

6. Dong, J., Wang, W., Tan, T.: Multi-class blind steganalysis based on image run-length analysis. In: Ho, A.T.S., Shi, Y.Q., Kim, H.J., Barni, M. (eds.) Digital Watermarking. LNCS, vol. 5703, pp. 199–210. Springer, Heidelberg (2009)

   Chapter  Google Scholar 

7. Fridrich, J.: Feature-based steganalysis for JPEG images and its implications for future design of steganographic schemes. In: Fridrich, J. (ed.) IH 2004. LNCS, vol. 3200, pp. 67–81. Springer, Heidelberg (2004)

   Google Scholar 

8. Fridrich, J., Goljan, M., Soukal, D., Holotyak, T.: Forensic steganalysis: determining the stego key in spatial domain steganography. In: Proceedings of the SPIE on Security and Watermarking of Multimedia Contents VII, vol. 5681, pp. 631–642 (2005)

   Google Scholar 

9. He, J., Huang, J.: Steganalysis of stochastic modulation steganography. Science in China Series F: Information Sciences 49(3), 273–285 (2006)

   Article  MATH  MathSciNet  Google Scholar 

10. Hsu, C.-W., Lin, C.-J.: A comparison of methods for multiclass support vector machines. IEEE Transactions on Neural Networks 13, 415–425 (2002)

    Article  Google Scholar 

11. Jiang, M., Wu, X., Wong, E., Memon, A.: Steganalysis of boundary-based steganography using autoregressive model of digital boundaries. In: IEEE International Conference on Multimedia and Expo, vol. 2, pp. 883–886 (2004)

    Google Scholar 

12. Liang, G.-l., Wang, S.-z., Zhang, X.-p.: Steganography in binary image by checking data-carrying eligibility of boundary pixels. Journal of Shanghai University (English Edition) 11(3), 272–277 (2007)

    Article  MathSciNet  Google Scholar 

13. Liu, Z., Ping, L., Chen, J., Wang, J., Pan, X.: Steganalysis based on differential statistics. In: Pointcheval, D., Mu, Y., Chen, K. (eds.) CANS 2006. LNCS, vol. 4301, pp. 224–240. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

14. Morkel, T., Eloff, J.H.P., Olivier, M.S.: Using image steganography for decryptor distribution. In: Meersman, R., Tari, Z., Herrero, P. (eds.) OTM 2006 Workshops. LNCS, vol. 4277, pp. 322–330. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

15. Noble, W.S.: What is a support vector machine? Nature biotechnology 24(12) (2006)

    Google Scholar 

16. Pan, H.-K., Chen, Y.-Y., Tseng, Y.-C.: A secure data hiding scheme for two-color images. In: 5th IEEE Symposium on Computers and Communications, pp. 750–755 (2000)

    Google Scholar 

17. Pevný, T., Fridrich, J.: Multi-class blind steganalysis for jpeg images. In: Proceedings of the SPIE on Security and Watermarking of Multimedia Contents VIII, vol. 6072(1), pp. 257–269 (2006)

    Google Scholar 

18. Pevny, T., Fridrich, J.: Merging markov and DCT features for multi-class jpeg steganalysis. In: Proceedings of the SPIE on Security and Watermarking of Multimedia Contents IX, vol. 6505(1), pp. 1–13 (2007)

    Google Scholar 

19. Provos, N.: Defending against statistical steganalysis. In: Proceedings of the 10th conference on USENIX Security Symposium, vol. 10, pp. 323–335 (2001)

    Google Scholar 

20. Rodriguez, B., Peterson, G.L.: Detecting steganography using multi-class classification. In: IFIP International Conference on Digital Forensics, vol. 242, pp. 193–204 (2007)

    Google Scholar 

21. Savoldi, A., Gubian, P.: Blind multi-class steganalysis system using wavelet statistics. In: 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, vol. 2, pp. 93–96 (2007)

    Google Scholar 

22. Shi, Y.Q., Chen, C., Chen, W.: A markov process based approach to effective attacking jpeg steganography. In: Camenisch, J.L., Collberg, C.S., Johnson, N.F., Sallee, P. (eds.) IH 2006. LNCS, vol. 4437, pp. 249–264. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

23. Tseng, Y.-C., Pan, H.-K.: Secure and invisible data hiding in 2-color images. In: Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies, vol. 2, pp. 887–896 (2001)

    Google Scholar 

24. Wang, P., Liu, F., Wang, G., Sun, Y., Gong, D.: Multi-class steganalysis for Jpeg stego algorithms. In: 15th IEEE International Conference on Image Processing, pp. 2076–2079 (2008)

    Google Scholar 

25. Westfeld, A.: F5-A steganographic algorithm. In: Moskowitz, I.S. (ed.) IH 2001. LNCS, vol. 2137, pp. 289–302. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

26. Wu, M., Liu, B.: Data hiding in binary image for authentication and annotation. IEEE transactions on multimedia 6(4), 528–538 (2004)

    Article  Google Scholar 

27. Yang, C.-Y.: Color image steganography based on module substitutions. In: 3rd IEEE International Conference on Intelligent Information Hiding and Multimedia Signal Processing, vol. 2, pp. 118–121 (2007)

    Google Scholar 

Download references