Experimental research of the software complex to attack the linguistic stegosystem
DOI:
https://doi.org/10.18372/2410-7840.20.12654Keywords:
software complex, linguistic steganography, counteracting the methods of steganography, semantic compression, textual steganography, automated steganalysis, linguistic systems of steganalysis, removal of hidden messageAbstract
Steganography, in particular linguistic steganography, acquires new forms due to the use of computer technologies and the Internet as well as the growing influence of information technologies on all spheres of human life. Modern methods of the textual information steganalysis are not intended for the purpose of efficiently use to attack the linguistic stegosystem, and the systems of automated text summarization do not take into account the possibility of steganographic techniques usage. The author implemented and pre-tested the software complex to attack the linguistic stegosystem on the basis of the method of the textual data compression for linguistic steganography. So, the final experimental research of the developed method implementation`s effectiveness is relevant. Therefore, the preliminary obtained data are specified in the work and the final conclusions about the effectiveness of the software complex and, accordingly, the method are presented. The experiment’s method based on the functional testing has been chosen and an additional module for evaluating experimental results has been developed. Thus, the preliminary results and conclusions were confirmed and the identified defects were corrected. The hypothesis about the stegomessage hidden in the text removal possibility by almost one hundred percent without loss of the semantic structure and the validity of assumptions about the impossibility of recovering the stegomessage after the modification of the text by the developed software complex is proved. As a result of comparison with analogues, it was proved that even though the developed system of steganalysis has shown a worse efficiency, it covers much wider range of investigated elements, which provides a significantly higher efficiency of the attack based on compression. The efficiency of using the developed method and software complex for steganography problems is proved.
References
І. М. Федотова-Півень, Я. В. Тарасенко «Шляхи задоволення потреб сучасної кібербезпеки в рамках протидії методам комп’ютерної лінгвістичної стеганографії», Безпека інформації, №23(3), С. 190-196, 2017.
Different Types of Software Testing And How It Improves The Software Quality [Електронний ресурс] – Режим доступу: https://www.spaceotechnologies.com/different-types-of-software-testing/
E. Günes, В. R. Radev «LexRank: graph-based lexical centrality as salience in text summarization», Journal of Artificial Intelligence Research, vol. 22 i. 1., pp. 457-479, 2004.
K. Gaines «15 Dummy Text Generators You Should Know» [Електронний ресурс] – Режим доступу: https://www.webdesignerdepot.com/2012/03/15-dummy-text-generators-you-should-know/
P. Meng, L. Hang, Z. Chen, Y. Hu, W. Yang, «STBS: A Statistical Algorithm for Steganalysis of Translation-Based Steganography», 12th International Conference «Information Hiding», Calgary, Canada, June 28-30, Vol. 6387, pp. 208-220, 2010.
R. Paulus, C. Xiong, R. Socher «A Deep Reinforced Model for Abstractive Summarization», arXiv preprint arXiv:1705.04304, May 2017 [Електронний ресурс] – Режим доступу: https://arxiv.org/abs/1705.04304
Z. Chen, L. Huang, Z. Yu, L. Li, W. Yang, «A Statistical Algorithm for Linguistic Steganography Detection Based on Distribution of Words», Third International Conference on Availability, Reliability and Security, Barcelona, Spain, March 04-07, pp. 558 – 563, 2008.
Z. Chen, L. Huang, Z. Yu, W. Yang, L. Li, X. Zheng, X. Zhao, «Linguistic Steganography Detection Using Statistical Characteristics of Correlations between Words», 10th International Workshop «Information Hiding», Santa Barbara, USA, May 19-21, Vol. 5284, pp. 224-235, 2008.
Z. Chen, L. Huang, Z. Yu, X. Zhao, X. Zhao, «Effective Linguistic Steganography Detection», 8th International Conference on Computer and Information Technology Workshops, Sidney, Australia, July 08-11, pp. 224-229, 2008.
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