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Reliable Pooled Steganalysis Using Fine-Grained Parameter Estimation and Hypothesis Testing

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Digital Forensics and Watermarking (IWDW 2016)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10082))

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Abstract

Despite the state-of-the-art steganalysis can detect highly undetectable steganography, it is too unreliable to implement in the real world due to its false alarm rate. In pooled steganalysis scenario, multiple objects are intercepted and a reliable collective decision is required. To control the reliability, the confidence intervals of the detectors’ false rates are estimated as a parameter and hypothesis testing technology is used to determine the threshold of stego rates. In view of the fact that the false rate is vulnerable to some image properties (e.g. image size, and texture complexity), we propose a novel fine-grained scheme where test sets are divided by its texture measure in both parameter estimation and hypothesis testing processes. The demonstration on public image sets shows the proposed scheme achieves higher reliability in most cases. It confirms that the priori knowledge of image properties is conductive to a accurate threshold and reliable decision.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant No. 61402390), the National Key Technology R&D Program (Grant No. 2014BAH41B01), and the Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDA06030600).

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Authors and Affiliations

  1. Software School, Xiamen University, Xiamen, 361005, China

    Wei Huang

  2. State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China

    Xianfeng Zhao

  3. University of Chinese Academy of Sciences, Beijing, 100049, China

    Xianfeng Zhao

Authors
  1. Wei Huang
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  2. Xianfeng Zhao
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Corresponding author

Correspondence to Wei Huang .

Editor information

Editors and Affiliations

  1. New Jersey Institute of Technology, Newark, New Jersey, USA

    Yun Qing Shi

  2. Korea University, Seoul, Korea (Republic of)

    Hyoung Joong Kim

  3. University of Vigo, Vigo, Spain

    Fernando Perez-Gonzalez

  4. Chinese Academy of Sciences, Beijing, China

    Feng Liu

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Huang, W., Zhao, X. (2017). Reliable Pooled Steganalysis Using Fine-Grained Parameter Estimation and Hypothesis Testing. 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_41

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  • DOI: https://doi.org/10.1007/978-3-319-53465-7_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53464-0

  • Online ISBN: 978-3-319-53465-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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