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A Steganalytic Scheme Based on Classifier Selection Using Joint Image Characteristics
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Author(s): Jie Zhu (State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China & School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China), Qingxiao Guan (State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China & School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China), Xianfeng Zhao (State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China & School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China), Yun Cao (State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China & School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China)and Gong Chen (State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China & School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China)
Copyright: 2017
Volume: 9
Issue: 4
Pages: 14
Source title:
International Journal of Digital Crime and Forensics (IJDCF)
Editor(s)-in-Chief: Feng Liu (Chinese Academy of Sciences, China)
DOI: 10.4018/IJDCF.2017100101
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Abstract
Steganalysis relies on steganalytic features and classification techniques. Because of the complexity and different characteristics of cover images, to make steganalysis more applicable toward detecting stego images in real applications, we need to train different classifiers so as to match different images according to their characteristics. Selection of classifiers according to characteristics of images is the key point to improve accuracy of steganalysis. In our work, we study the methods of classifier selection based on characteristics of images including image size, quantization factor, or matrix. Besides, we also discuss other characteristics, such as texture, cover source, which makes an appreciable difference to steganalysis.
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