Proceedings chapter
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English

Blind Statistical Steganalysis of Additive Steganography Using Wavelet Higher Order Statistics

Presented atSalzburg (Austria), Sep 19-21
PublisherSpringer
Collection
  • Lecture Notes in Computer Science; 3677
Publication date2005
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.

Keywords
  • Watermarking
  • Data Encryption
  • Computer Communication Networks
  • Multimedia Information Systems
  • Information Systems Applications (incl. Internet)
  • Management of Computing and Information Systems
  • Computers and Society
Citation (ISO format)
HOLOTYAK, Taras, FRIDRICH, Jessica, VOLOSHYNOVSKYY, Svyatoslav. Blind Statistical Steganalysis of Additive Steganography Using Wavelet Higher Order Statistics. In: 9th IFIP TC-6 TC-11 Conference on Communications and Multimedia Security (CMS 2005). Salzburg (Austria). [s.l.] : Springer, 2005. p. 273–274. (Lecture Notes in Computer Science) doi: 10.1007/11552055_31
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Additional URL for this publicationhttp://link.springer.com/book/10.1007%2F11552055
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