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Cover-aware Steganalysis

 
: Bunzel, Niklas; Steinebach, Martin; Liu, Huajian

:

Journal of Cyber Security and Mobility 10 (2021), No.1, pp.1-26
ISSN: 2245-1439 (Print)
ISSN: 2245-4578 (Online)
English
Journal Article
Fraunhofer SIT ()

Abstract
The increasing digitization offers new ways, possibilities and needs for a secure transmission of information. Steganography and its analysis constitute an essential part of IT-Security. In this work we show how methods of blind-steganalysis can be improved to work in cover-aware scenarios, we will call this non-blind steganalysis. The main objective was to examine how to take advantage of the knowledge of reference images to maximize the accuracy-rate of the analysis.
Therefore we evaluated common stego-tools and their embedding algorithms and established a dataset of 353110 images. The images have been applied to test the potency of the improved methods of the non-blind steganalysis. The results show that the accuray can be significantly improved by using cover-images to produce reference images. Also the aggregation of the outcomes has shown to have a positive impact on the accuracy. Particularly noteworthy is the correlation between the qualities of the stego- and coverimages. Only by consindering both, the accuracy could strongly be improved. Interestingly the difference between both qualities also has a deep impact on the results.

: http://publica.fraunhofer.de/documents/N-633435.html