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http://dx.doi.org/10.3837/tiis.2014.11.028

Recognizing F5-like stego images from multi-class JPEG stego images  

Lu, Jicang (Zhengzhou Information Science and Technology Institute)
Liu, Fenlin (State key Laboratory of Mathematical Engineering and Advanced Computing)
Luo, Xiangyang (State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.8, no.11, 2014 , pp. 4153-4169 More about this Journal
Abstract
To recognize F5-like (such as F5 and nsF5) steganographic algorithm from multi-class stego images, a recognition algorithm based on the identifiable statistical feature (IDSF) of F5-like steganography is proposed in this paper. First, this paper analyzes the special modification ways of F5-like steganography to image data, as well as the special changes of statistical properties of image data caused by the modifications. And then, by constructing appropriate feature extraction sources, the IDSF of F5-like steganography distinguished from others is extracted. Lastly, based on the extracted IDSFs and combined with the training of SVM (Support Vector Machine) classifier, a recognition algorithm is presented to recognize F5-like stego images from images set consisting of a large number of multi-class stego images. A series of experimental results based on the detection of five types of typical JPEG steganography (namely F5, nsF5, JSteg, Steghide and Outguess) indicate that, the proposed algorithm can distinguish F5-like stego images reliably from multi-class stego images generated by the steganography mentioned above. Furthermore, even if the types of some detected stego images are unknown, the proposed algorithm can still recognize F5-like stego images correctly with high accuracy.
Keywords
Steganalysis; Recognition of stego images; F5; nsF5; Identifiable statistical feature;
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