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Parameter-estimation and algorithm-selection based United-Judgment for image steganalysis

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Abstract

In order to synthetically utilize multiple steganalytic algorithms, and further improve the detection accuracy and enhance detection reliability, United-Judgment methods are researched and analyzed in this paper. According to the performance of each algorithm, United-Judgment methods for both blind and specific steganalysis are proposed based on parameter-estimation and algorithm-selection. Experiments are carried out for the former with seven typical blind detections and the latter one with five typical spatial domain steganalytic methods. Experimental results show that the proposed methods can synthetically utilize the existing multiple algorithms effectively, and achieve more reliable detection.

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Acknowledgments

The authors are grateful to the technical committee of the International Conference on Multimedia Information Networking and Security 2009 for recommending this paper to the International Journal. They are also grateful to Dr. Shiguo Lian for his insightful and invaluable suggestions and comments.

This work is supported by the National Natural Science Foundation of China (Grant No. 60970141 and 60902102), the Found of Innovation Scientists and Technicians Troop Construction Projects of Henan Province (Grand No. 094200510008) and the Science and Technology Program of Zhengzhou City (Grant No. 083SGYG21125).

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Authors and Affiliations

  1. Institute of Information Science and Technology, Zhengzhou, 450002, China

    Jicang Lu, Fenlin Liu, Xiangyang Luo & Chunfang Yang

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  1. Jicang Lu
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  2. Fenlin Liu
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  3. Xiangyang Luo
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  4. Chunfang Yang
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Correspondence to Jicang Lu.

Additional information

Part of the content of this paper has been published in IEEE Proceedings of International Conference on Multimedia Information Networking and Security, 2009.

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Lu, J., Liu, F., Luo, X. et al. Parameter-estimation and algorithm-selection based United-Judgment for image steganalysis. Multimed Tools Appl 57, 91–107 (2012). https://doi.org/10.1007/s11042-010-0588-x

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