Abstract
Most of the existing distortion functions for digital images steganography allot a same embedding cost for ±1 embedding change, which should be different intuitively. This paper proposes a general method to distinguish the embedding cost for different polarity of embedding change for spatial images. The fluctuation after pixels are +1 or −1 modified respectively, and the texture of cover image are employed to adjust a given distortion function. After steganography with the adjusted distortion function, the fluctuation around stego pixels become more similar to the fluctuation around their neighbourhoods. This similarity performs less detectable artifacts. Experiment results show that the statistical undetectability of current popular steganographic methods is increased after incorporated the proposed method.
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References
Ker, A., et al.: Moving steganography and steganalysis from the laboratory into the real world. In: Proceedings of the First ACM Workshop on Information Hiding and Multimedia Security, New York, NY, USA, pp. 45–58, June 2013
Li, B., Tan, S., Wang, M., Huang, J.: Investigation on cost assignment in spatial image steganography. IEEE Trans. Inf. Forensics Secur. 9(2), 1264–1277 (2014)
Li, B., Wang, M., Li, X., Tan, S., Huang, J.: A strategy of clustering modification directions in spatial image steganography. IEEE Trans. Inf. Forensics Secur. 10(9), 1905–1917 (2015)
Frdrich, J., Soukal, D.: Matrix embedding for large payloads. In: Proceedings of the International Society for Optics and Photonics, San Jose, CA, pp. 60721W–60721W-12, February 2006
Zhang, X., Wang, S.: Efficient steganographic embedding by exploiting modification direction. IEEE Commun. Lett. 10(11), 781–783 (2006)
Zhang, W., Zhang, X., Wang, S.: Maximizing steganographic embedding efficiency by combining hamming codes and wet paper codes. In: Solanki, K., Sullivan, K., Madhow, U. (eds.) IH 2008. LNCS, vol. 5284, pp. 60–71. Springer, Heidelberg (2008). doi:10.1007/978-3-540-88961-8_5
Filler, T., Judas, J., Fridrich, J.: Minimizing additive distortion in steganography using syndrome-trellis codes. IEEE Trans. Inf. Forensics Secur. 6(3), 920–935 (2011)
Pevný, T., Filler, T., Bas, P.: Using high-dimensional image models to perform highly undetectable steganography. In: Böhme, R., Fong, P.W.L., Safavi-Naini, R. (eds.) IH 2010. LNCS, vol. 6387, pp. 161–177. Springer, Heidelberg (2010). doi:10.1007/978-3-642-16435-4_13
Holub, V., Fridrich, J.: Designing steganographic distortion using directional filters. In: Proceedings of the IEEE International Workshop on Information Forensics and Security, Binghamton, NY, USA, pp. 234–239, December 2012
Holub, V., Fridrich, J.: Digital image steganography using universal distortion. In: Proceedings of the First ACM Workshop on Information Hiding and Multimedia Security, New York, NY, USA, pp. 59–68, June 2013
Holub, V., Fridrich, J., Denemark, T.: Universal distortion function for steganography in an arbitrary domain. EURASIP J. Inf. Secur. 2014(1), 1–13 (2014)
Li, B., Wang, M., Huang, J., Li, X.: A new cost function for spatial image steganography. In: Proceedings of the IEEE International Conference on Image Processing, Paris, France, pp. 4206–4210, October 2014
Sedighi, V., Fridrich, J., Cogranne, R.: Content-adaptive pentary steganography using the multivariate generalized gaussian cover model. In: Proceedings of the International Society for Optics and Photonics, San Francisco, California, USA, pp. 94090H–94090H-13, March 2015
Sedighi, V., Fridrich, J.: Effect of saturated pixels on security of steganographic schemes for digital images. In: Proceedings of the IEEE International Conference on Image Processing, Phoenix, Arizona, USA, pp. 25–28, September 2016
Bas, P., Filler, T., Pevný, T.: “Break our steganographic system”: the ins and outs of organizing BOSS. In: Filler, T., Pevný, T., Craver, S., Ker, A. (eds.) IH 2011. LNCS, vol. 6958, pp. 59–70. Springer, Heidelberg (2011). doi:10.1007/978-3-642-24178-9_5
Pevny, T., Bas, P., Fridrich, J.: Steganalysis by subtractive pixel adjacency matrix. IEEE Trans. Inf. Forensics Secur. 5(2), 215–224 (2010)
Denemark, T., Fridrich, J., Holub, V.: Further study on the security of S-UNIWARD. In: Proceedings of the SPIE, Electronic Imaging, Media Watermarking, Security, and Forensics, San Francisco, CA, pp. 902805–902805-13, February 2014
Fridrich, J., Kodovsky, J.: Rich models for steganalysis of digital images. IEEE Trans. Inf. Forensics Secur. 7(3), 868–882 (2012)
Kodovsky, J., Fridrich, J., Holub, V.: Ensemble classifiers for steganalysis of digital media. IEEE Trans. Inf. Forensics Secur. 7(2), 432–444 (2012)
Denemark, T., Fridrich, J.: Improving steganographic security by synchronizing the selection channel. In: Proceedings of the 3rd ACM Workshop on Information Hiding and Multimedia Security, New York, NY, USA, pp. 5–14, June 2015
Acknowledgment
This work was supported by the Natural Science Foundation of China (61525203, 61472235, and 61502009), the Program of Shanghai Dawn Scholar (14SG36) and Shanghai Academic Research Leader (16XD1401200).
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Wang, Z., Lv, J., Wei, Q., Zhang, X. (2017). Distortion Function for Spatial Image Steganography Based on the Polarity of Embedding Change. In: Shi, Y., Kim, H., Perez-Gonzalez, F., Liu, F. (eds) Digital Forensics and Watermarking. IWDW 2016. Lecture Notes in Computer Science(), vol 10082. Springer, Cham. https://doi.org/10.1007/978-3-319-53465-7_36
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DOI: https://doi.org/10.1007/978-3-319-53465-7_36
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