Abstract
Syndrome-Trellis Codes (STCs) have been widely used in adaptive steganography due to their high embedding efficiency. However, this type of steganographic codes is sensitive to stego damage, which may be incurred by compression, channel noise, active attacks, and so on, in practical covert communication. In this paper, a construction of robust STCs is proposed to achieve a good balance between robustness and embedding efficiency. The encoder of the proposed scheme performs a specified Error Correction Code (ECC) on the STC’s intermediate outputs. Further, a Viterbi algorithm is suggested to effectively find the optimum stego vector. At the extraction phase, the received stego vector is first decoded by the decoder of the employed ECC and then sent to the STC decoder, which gives the extracted message bits. Experimental results show the proposed scheme presents a good robustness performance, meanwhile the stego remains an acceptable detection resistance against steganalyzers.
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Acknowledgements
This work was supported by the Key R&D Program of Guangdong Province (Grant No. 2019B010136003), National Key R&D Program of China (Grant No. 2017YFB0802200), National Natural Science Foundation of China (Grant No. 61802145), Natural Science Foundation of Guangdong Province, China (Grant No. 2017A-030313390, 2018A030313387), Science and Technology Program of Guangzhou, China (Grant No. 201804010428), the Fundamental Research Funds for the Central Universities, the Opening Project of State Key Laboratory of Information Security, the Opening Project of Guangdong Provincial Key Laboratory of Information Security Technology (Grant No. 2017B030314131), the Opening Project of Guangdong Key Laboratory of Intelligent Information Processing and Shenzhen Key Laboratory of Media Security.
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Feng, B., Liu, Z., Wu, X., Lin, Y. (2020). Robust Syndrome-Trellis Codes for Fault-Tolerant Steganography. In: Jain, L., Peng, SL., Wang, SJ. (eds) Security with Intelligent Computing and Big-Data Services 2019. SICBS 2019. Advances in Intelligent Systems and Computing, vol 1145. Springer, Cham. https://doi.org/10.1007/978-3-030-46828-6_11
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DOI: https://doi.org/10.1007/978-3-030-46828-6_11
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