Abstract
Digital image steganography is one of the important ways to achieve covert communication to protect users’ data privacy. Steganalysis technology is the key technology to check the security of steganography, and the extraction of embedded messages is an important challenge for image steganalysis technology. Existing methods are for plain text embedding or only for certain special scenarios, they are not applicable to the extraction under the known cover image. To this end, this paper proposes a method of extracting embedded messages under the condition of the known cover images. First, the STCs encoding process is analyzed using the syndrome trellis. Second, a path in the syndrome trellis can be obtained by using the stego sequence and a certain parity-check matrix. Meanwhile, the embedding process can also be partially simulated using the cover sequence and the parity-check matrix. By comparing whether the paths are consistent, the coding parameters can be quickly filtered to find the correct submatrices and extract the correct embedded messages. This algorithm avoids the second embedding of all possible secret messages, which significantly improves the efficiency of coding parameter recognition. The experimental results show that the proposed method can identify STCs parameters of stego images using HUGO steganography in a short time, so as to realize the extraction of embedded messages.
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References
Wayner, P.: Disappearing Cryptography: Information Hiding: Steganography and Watermarking. Morgan Kaufmann, Burlington (2009)
Cheddad, A., Condell, J., Curran, K., et al.: Digital image steganography: survey and analysis of current methods. Sig. Process. 90(3), 727–752 (2010)
Filler, T, Judas, J, Fridrich, J.: Minimizing embedding impact in steganography using trellis-coded quantization. In: Proceedings of SPIE, Media Forensics and Security II[C], SPIE 7541, pp. 0501–0514 (2010)
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). https://doi.org/10.1007/978-3-642-16435-4_13
Holub, V., Fridrich, J.: Designing steganographic distortion using directional filters. In: Proceedings of the 4th IEEE International Workshop on Information Forensics and Security, pp. 234–239 (2012)
Holub, V., Fridrich, J.: Digital image steganography using universal distortion. In: Proceedings of the 1st ACM Information Hiding and Multimedia Security Workshop, pp. 59–68 (2013)
Li, B., Wang, M., Huang, J., et al.: A new cost functions for spatial image steganography. In: Proceeding of 21st IEEE International Conference on Image Processing, pp. 4206–4210 (2014)
Sedighi, V., Cogranne, R., Fridrich, J.: Content-adaptive steganography by minimizing statistical detectability. IEEE Trans. Inf. Forensics Secur. 11(2), 221–234 (2016)
Filler, T., Fridrich, J.: Design of adaptive steganographic schemes for digital images. In: Proceedings of SPIE, Electronic Imaging, Media Watermarking, Security, and Forensics XIII, SPIE 7880, pp. 0F01–0F14 (2011)
Guo, L., Ni, J., Shi, Y.Q.: An efficient JPEG steganographic scheme using uniform embedding. In: Proceedings of the 4th IEEE International Workshop on Information Forensics and Security, pp. 169–174 (2012)
Guo, L., Ni, J., Su, W., et al.: Using statistical image model for jpeg steganography: uniform embedding revisited. IEEE Trans. Inf. Forensics Secur. 10(12), 2669–2680 (2015)
Liu, W., Liu, G., Dai, Y.: On recovery of the stego-key in syndrome-trellis codes. Innov. Comput. Inf. Control Express Lett. 8(10), 2901–2906 (2014)
Luo, X., Song, X., Li, X., et al.: Steganalysis of HUGO steganography based on parameter recognition of syndrome-trellis-codes. Multimedia Tools Appl. 75(21), 13557–13583 (2016)
Gan, J., Liu, J., Luo, X., et al.: Reliable steganalysis of HUGO steganography based on partially known plaintext. Multimedia Tools Appl. 8, 1–21 (2017)
Kodovský, J., Fridrich, J.: Quantitative steganalysis using rich models. In: Proceedings of SPIE, Electronic Imaging, Media Watermarking, Security and Forensic XV, SPIE 8665, pp. 86650O (2013)
Acknowledgement
This work was supported by the National Natural Science Foundation of China (No. U1804263, 61772549).
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Li, J., Luo, X., Zhang, Y., Zhang, P., Yang, C., Liu, F. (2020). Steganalysis of Adaptive Steganography Under the Known Cover Image. In: Yu, S., Mueller, P., Qian, J. (eds) Security and Privacy in Digital Economy. SPDE 2020. Communications in Computer and Information Science, vol 1268. Springer, Singapore. https://doi.org/10.1007/978-981-15-9129-7_39
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DOI: https://doi.org/10.1007/978-981-15-9129-7_39
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