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

  • Wei HuangEmail author
  • Xianfeng Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10082)

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.

Keywords

Steganalysis Steganography Parameter estimation Hypothesis testing 

Notes

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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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Software SchoolXiamen UniversityXiamenChina
  2. 2.State Key Laboratory of Information Security, Institute of Information EngineeringChinese Academy of SciencesBeijingChina
  3. 3.University of Chinese Academy of SciencesBeijingChina

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