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Multi-modal Steganography Based on Semantic Relevancy

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Digital Forensics and Watermarking (IWDW 2020)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12617))

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Abstract

Traditional steganography embeds confidential information by modifying the carrier at the symbol level, e.g., the pixels of an image or the words of a text. Since modification traces will inevitably be left on the carrier, it is hard to resist the detection of the steganalysis algorithms. To address this problem, this paper proposes a novel steganographic framework called multi-modal steganography, which hides secret messages at the semantic level. In this framework, multi-modal covers are projected into a common semantic space, in which their relevancy can be measured. The confidential information can be embedded in the semantic relevancy among the covers with a relevancy-message mapping algorithm. By choosing and sending a series of original multi-modal covers, the secret messages are transmitted to the receiver. In this paper, we adopt text and image as the two modalities. A visual semantic embedding model is utilized to measure the relevancy between the texts and images. Both the theoretical analysis and experiments demonstrate that the proposed multi-modal steganography has good resistance to the existing steganalysis methods and high quality of concealment.

This research is supported by the National Key R&D Program (2018YFB0804103) and the National Natural Science Foundation of China (No. U1705261 and No. U1836204).

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Authors and Affiliations

  1. Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China

    Yuting Hu, Zhongliang Yang, Han Cao & Yongfeng Huang

  2. Beijing National Research Center for Information Science and Technology, Beijing, 100084, China

    Yuting Hu, Zhongliang Yang & Yongfeng Huang

Authors
  1. Yuting Hu
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  2. Zhongliang Yang
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  3. Han Cao
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  4. Yongfeng Huang
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Corresponding author

Correspondence to Zhongliang Yang .

Editor information

Editors and Affiliations

  1. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

    Xianfeng Zhao

  2. Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA

    Yun-Qing Shi

  3. Department of Information Engineering, University of Florence, Florence, Italy

    Alessandro Piva

  4. School of Cybersecurity, Korea University, Seoul, Korea (Republic of)

    Hyoung Joong Kim

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Hu, Y., Yang, Z., Cao, H., Huang, Y. (2021). Multi-modal Steganography Based on Semantic Relevancy. In: Zhao, X., Shi, YQ., Piva, A., Kim, H.J. (eds) Digital Forensics and Watermarking. IWDW 2020. Lecture Notes in Computer Science(), vol 12617. Springer, Cham. https://doi.org/10.1007/978-3-030-69449-4_1

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  • DOI: https://doi.org/10.1007/978-3-030-69449-4_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-69448-7

  • Online ISBN: 978-3-030-69449-4

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