Blind statistical steganalysis of additive steganography using wavelet higher order statistics

Authors:
Taras Holotyak;Jessica Fridrich;Sviatoslav Voloshynovskiy
Affiliations:
Department of Electrical and Computer Engineering, State University of New York at, Binghamton, Binghamton, NY;Department of Electrical and Computer Engineering, State University of New York at, Binghamton, Binghamton, NY;Department of Computer Science, University of Geneva, Geneva 4, Switzerland
Venue:
CMS'05 Proceedings of the 9th IFIP TC-6 TC-11 international conference on Communications and Multimedia Security
Year:
2005

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Abstract

Development of digital communications systems significantly extended possibility to perform covert communications (steganography). This recalls an emerging demand in highly efficient counter-measures, i.e. steganalysis methods. Modern steganography is presented by a broad spectrum of various data-hiding techniques. Therefore development of corresponding steganalysis methods is rather a complex problem and challenging task. Moreover, in many practical steganalysis tasks second Kerckhoff's principle is not applicable because of absence of information about the used steganography method. This motivates to use blind steganalysis, which can be applied to the certain techniques where one can specify at least statistics of the hidden data. This paper focuses on the class of supervised steganalysis techniques developed for the additive steganography, which can be described as y = f(x, s, K) = x + g(s, K), where stego image y is obtained from the cover image x by adding a low-amplitude cover image independent ((1 embedding also known as LSB matching) or cover image dependent (LSB embedding) stego signals that may be also depended on secret stego key K and the secret data s. The function g(.) represents the embedding rule.