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Blind Steganalysis: Estimation of Hidden Message Length
Author(s) -
Sanjay Kumar Jena,
G. Vamsi Krishna
Publication year - 2007
Publication title -
international journal of computers communications and control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.422
H-Index - 33
eISSN - 1841-9844
pISSN - 1841-9836
DOI - 10.15837/ijccc.2012.2.2348
Subject(s) - steganalysis , steganography , histogram , computer science , pattern recognition (psychology) , rendering (computer graphics) , embedding , artificial intelligence , least significant bit , information hiding , image (mathematics) , computer vision , operating system
Steganography is used to hide the occurrence of communication. Dis- covering and rendering useless such covert message is an art of steganalysis. The importance of techniques that can reliably detect the presence of secret messages in images is increasing as images can hide a large amount of malicious code that could be activated by a small Trojan horse type of virus and also for tracking criminal ac- tivities over Internet. This paper presents an improved blind steganalysis technique. The proposed algorithm reduces the initial-bias, and estimates the LSB embedding message ratios by constructing equations with the statistics of difference image his- togram. Experimental results show that this algorithm is more accurate and reliable than the conventional difference image histogram method. It outperforms other pow- erful steganalysis approaches for embedded ratio greater than 40% and comparable

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