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Feature learning for steganalysis using convolutional neural networks

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Abstract

Traditional steganalysis methods usually rely on handcrafted features. However, with the rapid development of advanced steganography, manual design of complex features has become increasingly difficult. In this paper, we propose a new paradigm for steganalysis based on the concept of feature learning. In our method, Convolutional Neural Network (CNN) is used to automatically learn features for steganalysis. To make CNN work better for steganalysis, we incorporate domain knowledge of steganalysis (i.e. enhancing stego noise and exploiting nearby dependencies) when designing the CNN architectures. We further propose to use model combination to boost the performance of CNN based method. Additionally, a cropping strategy is proposed to enable the CNN based model to deal with arbitrary input image sizes. We demonstrate the effectiveness of the proposed method against state-of-the-art spatial domain steganographic algorithms such as HUGO, WOW, S-UNIWARD, MiPOD, and HILL-CMD. To help understand the learned features from CNN, we provide visualizations of the learned filters and feature maps. Finally, we also provide quantitative analysis of the learned features from convolutional layers.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China under Grant 61772529, 61303262, 61502496, U1536120, and U1636201, and in part by the National Key Research and Development Program of China under Grant 2016YFB1001003.

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Authors and Affiliations

  1. Department of Automation, University of Science and Technology of China, 96 JinZhai Road, 230026, Hefei, China

    Yinlong Qian

  2. Center for Research on Intelligent Perception and Computing, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, 100190, Beijing, China

    Yinlong Qian, Jing Dong, Wei Wang & Tieniu Tan

  3. State Key Laboratory of Cryptology, P.O. Box 5159, Beijing, 100878, China

    Wei Wang

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  1. Yinlong Qian
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  2. Jing Dong
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  4. Tieniu Tan
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Correspondence to Jing Dong.

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Qian, Y., Dong, J., Wang, W. et al. Feature learning for steganalysis using convolutional neural networks. Multimed Tools Appl 77, 19633–19657 (2018). https://doi.org/10.1007/s11042-017-5326-1

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  • DOI: https://doi.org/10.1007/s11042-017-5326-1

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