STBS: a statistical algorithm for steganalysis of translation-based steganography

Authors:
Peng Meng;Liusheng Hang;Zhili Chen;Yuchong Hu;Wei Yang
Affiliations:
NHPCC, Depart. of CS. & Tech., USTC, Hefei, China;NHPCC, Depart. of CS. & Tech., USTC, Hefei, China and Suzhou Institute for Advanced Study, USTC, Suzhou, China;NHPCC, Depart. of CS. & Tech., USTC, Hefei, China and Suzhou Institute for Advanced Study, USTC, Suzhou, China;NHPCC, Depart. of CS. & Tech., USTC, Hefei, China;NHPCC, Depart. of CS. & Tech., USTC, Hefei, China and Suzhou Institute for Advanced Study, USTC, Suzhou, China
Venue:
IH'10 Proceedings of the 12th international conference on Information hiding
Year:
2010

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Abstract

Translation-Based Steganography is a secure text steganographic algorithm. In this paper, we present a novel statistical algorithm for steganalysis of Translation-Based Steganography (STBS). We first show that there are fewer high-frequency words in stegotexts than in normal texts. We then design a preprocessor to refine all the given texts to expand the frequency differences between normal texts and stegotexts. 12 dimensional feature vectors sensitive to frequency are derived from the refined texts. We finally use a SVM classifier to classify given texts to normal texts and stegotexts. A series of experiments is given to demonstrate the performance of STBS.