Modeling steganocontent extraction attempts with different lengths stack sampling series of images blocks

Keywords: run-lengths encoding, steganography, content, hacking, stack

Abstract

The results obtained by using different lengths of sample stacks of runs in simulating the attempts of unauthorized extraction (attack) of steganocontent "protected" by implementing the mechanism of inter-block multiplexing of the parameters of the run lengths of image blocks have been considered in the article. The relationship between the parameters of processing the content (namely, halftone images) and the number of series, as well as the combinatorics of the component elements of the obtained pairs of series parameters, which are the objects of inter-block multiplexing has been demonstrated. It is concluded that the simultaneous use of 2-level data multiplexing significantly extends the capabilities to withstand content attack attempts. It has been found that the use of blocks of higher dimensionality, significantly reduces the role current parameters of the series reliance (base) blocks, in breaking the structure of the original images (those. original content). It is noted that use of two levels of multiplexing of output data at once significantly increases the resistance of the content to attempts at its unauthorized extraction, leading to large distortions in the attacked image, in case of incorrect selection of the active processing parameters.

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Author Biographies

Mykyta Honcharov, V. N. Karazin Kharkiv National University

Computer science student (Magistrate)

Larysa Pavlova, V. N. Karazin Kharkiv National University

Senior Lecturer, Department of Foreign Languages for Professional Purposes, Faculty of Foreign Languages

Yulia Lesnaya, V. N. Karazin Kharkiv National University

5rd year student, Faculty of Computer Science

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Published
2022-12-26
Cited
How to Cite
Honcharov, M., Pavlova, L., & Lesnaya, Y. (2022). Modeling steganocontent extraction attempts with different lengths stack sampling series of images blocks. Computer Science and Cybersecurity, (2), 22-27. https://doi.org/10.26565/2519-2310-2022-2-02
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