Experimental evaluation of the text documents marking algorithm based on interword distances shifting

The article presents the experimental parameter evaluation results of the electronic documents marking algorithm, based on interword distances shifting. The developed marking algorithm is designed to increase the security of electronic documents containing textual information from leakage through channels caused by printing, scanning or photographing, followed by sending the generated image. The algorithm analyzed parameters are such characteristics as embedding capacity, invisibility, undetectability, extractability and robustness. In the course of embedding capacity estimation of the developed algorithm, analytical expressions are given that make it possible to calculate the maximum achievable embedding capacity value. The obtained quantitative estimates and the experiments carried out made it possible to substantiate the admissible values choice of the embedded marker. To determine the embedded information invisibility in the source document, an invisibility and undetectability assessment of the embedded marker was carried out. During the expert evaluation, the developed algorithm invisibility to visual analysis was substantiated, as well as the absence of significant statistical deviations in the distribution of the analyzed parameters in the process of assessing the resistance of the developed marking algorithm to the potentially best steganographic analysis method. The quantitative extractability of the developed marking algorithm was carried out by assessing the extraction accuracy. The analysis performed showed accuracy high values of marker extraction from scanned images, which makes it possible to reliably extract embedded data, as well as determine directions for improving the extraction accuracy from photographed images. In the assessing process the stability of the developed marking algorithm to the transformations implementation and distortions introduction, the main robustness parameters of the developed marking algorithm to the printing, scanning and photographing processes are determined. Conclusions are formulated on the using possibility the developed marking algorithm and directions for further researches are identified.

1. Cybersecurity threatscape: Year 2021 in review. Positive Technologies, 2022, 23 p. Available at: https://www.ptsecurity.com/upload/corporate/ww-en/analytics/Cybersecurity_threatscape_2021_ENG.pdf, accessed 10.08.2022.

2. Отчёт об исследовании утечек информации ограниченного доступа в 2021 году. InfoWatch, 2022 г., 32 стр. / Restricted Information Leakage Study Report in 2021. InfoWatch. 2021, 32 p. Available at: https://www.infowatch.ru/analytics/analitika/v-2021-stalo-bolshe-umyshlennykh-utechek, accessed 10.08.2022 (in Russian).

3. Jain M., Lenka S.K. A Review on Data Leakage Prevention using Image Steganography. International Journal of Computer Science Engineering, vol. 5, no 2, 2016, pp 56-59.

4. Lopez G., Richardson N., Carvajal J. Methodology for Data Loss Prevention Technology Evaluation for Protecting Sensitive Information. Revista Politecnican, vol. 36, no 3, 2015, pp. 60-69.

5. Alneyadi S., Sithirasenan E., Muthukkumarasamy V. A survey on data leakage prevention systems. Journal of Network and Computer Applications, vol. 62, 2016, pp. 137-152.

6. Jadhav P., Chawan P.M. Data Leak Prevention system: A Survey. International Research Journal of Engineering and Technology, vol. 6, no. 10, 2019, pp. 197-199.

7. Козачок А.В., Копылов С.А. и др. Алгоритм маркирования текстовых документов на основе изменения интервалов между словами, обеспечивающий устойчивость к преобразованию формата. Труды ИСП РАН, том 5, вып. 5, 2021 г., стр. 131-146. DOI: 10.15514/ISPRAS-2021-33(4)-10. / Kozachok A.V., Kopylov S.A. et al. Text documents marking algorithm based on interword distances shifting invariant to format conversion. Trudy ISP RAN/Proc. ISP RAS, vol. 33, issue 4, 2021, pp. 131-146 (in Russian).

8. Kozachok A.V., Kopylov S.A. et al. Text marking approach for data leakage prevention. Journal of Computer Virology and Hacking Techniques, vol. 15, no. 3, 2019, pp. 219-232.

9. Salomon D. Data privacy and security: encryption and information hiding. Springer Science & Business Media, New York, 2003. 469 p.

10. Kapila B., Thind T. Review and analysis of data security using image steganography. In Proc. of the 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM), 2021, pp.227-231.

11. Woo C.-S. Digital image watermarking methods for copyright protection and authentication. PhD Thesis. Information Security Institute, Faculty of Information Technology, Queensland University of Technology, 2007, 197 p.

12. Mohanarathinam A., Kamalraj S. et al. Digital watermarking techniques for image security: a review. Journal of Ambient Intelligence and Humanized Computing, vol. 11, 2020, pp. 3221-3229.

13. Khadam U., Iqbal M.M. et al. Digital Watermarking Technique for Text Document Protection Using Data Mining Analysis. IEEE Access, vol. 7, 2019, pp. 64955-64965.

14. Kozachok A.V., Kopylov S.A. Estimation of Watermark Embedding Capacity with Line Space Shifting. In Proc. of the Ivannikov Memorial Workshop (IVMEM), 2020, pp. 29-34.

15. Национальный стандарт Российской Федерации. Система стандартов по информации, библиотечному и издательскому делу. Организационно-распорядительная документация. Требования к оформлению документов. ГОСТ Р 7.0.97–2016, Стандартинформ, 2019 г., 32 стр. / National standard of the Russian Federation, System of standards on information, librarianship and publishing. Organizational and administrative documentation. Requirements for presentation of recordsю GOST R 7.0.97–2016, Standartinform, 2019, 32 p. (in Russian).

16. Zhou N.R., Hou W.M.X., Wen R.H. Imperceptible digital watermarking scheme in multiple transform domains. Multimedia Tools and Applications, vol. 77, 2018, pp. 30251–30267.

17. Wu J.Y., Huang W.L., Xia-Hou W.M. Imperceptible digital watermarking scheme combining 4-level discrete wavelet transform with singular value decomposition. Multimedia Tools and Applications, vol. 79, 2020, pp. 22727–22747.

18. Грибунин В.Г., Оков И.Н., Туринцев И.В. Цифровая стеганография. Москва, СОЛОН-Пресс, 2017 г., 262 стр. / Gribunin V.G., Okov I.N., Turincev I.V. Digital steganography. Moscow, SOLON-Press, 2017, 262 p. (in Russian).

19. Коржик В.И. Цифровая стеганография и цифровые водяные знаки. Санкт-Петербург, СПбГУТ, 2017 г., 424 стр. / Korzhik V.I. Digital Steganography and Digital Watermarking. Saint-Petersburg, SPbSUT, 2016, 226 p. (in Russian)

20. Козачок А.В., Копылов С.А., Бочков М.В. Оценка параметров необнаруживаемости разработанного подхода к маркированию текстовых электронных документов. Вопросы кибербезопасности, no. 1(35), 2020, стр. 62-73 / Kozachok A.V., Kopylov S.A., Bochkov M.V. Undetectability Parameters Estimation of the Developed Approach to Text Electron Documents Marking. no 1(35), 2020, pp. 62-73 (in Russian).

21. Karampidis K., Kavallieratou E., Papadourakis G. A review of image steganalysis techniques for digital forensics. Journal of Information Security and Applications, vol. 40, 2018, pp. 217-235.

22. Yang Z., Huang Y., Zhang Y.-J. A fast and efficient text steganalysis method. IEEE Signal Processing Letters, vol. 26, no. 4, 2019, pp. 627-631.

23. Kadian P., Arora S.M., Arora N. Robust Digital Watermarking Techniques for Copyright Protection of Digital Data: A Survey. Wireless Personal Communications, vol. 118, 2021, pp. 3225-3249.

24. Menendez-Ortiz A., Feregrino-Uribe C. et al. A Survey on Reversible Watermarking for Multimedia Content: A Robustness Overview, IEEE Access, vol. 7, 2019, pp. 132662-132681.