Метод защиты информации цифровых документов с помощью невидимых цифровых меток и его реализация
Аннотация
В настоящее время многие цифровые данные, которые передаются через Интернет, часто подвергаются атакам злоумышленников, что приводит к утечке информации и создает серьезные проблемы в области защиты авторского права, защиты права собственности, аутентификации и т.д. В последние годы большое внимание пользователей и исследователей привлекла технология цифровых водяных меток для применения в задачах защиты контента. Особенно требовательной областью цифрового маркирования являются методы маркирования документов, которые очень чувствительны к любым изменениям текста. В данной статье рассматриваются текущие тенденции в области технологий нанесения и извлечения водяных меток на цифровые документы, чтобы определить самые современные методы и их ограничения. Также разрабатывается общая архитектура алгоритма нанесения и алгоритма извлечения надежных и незаметных водяных меток в документ, основанная на изменении глифов текста, для решения проблемы отслеживания источника утечки информации. Применяя такой алгоритм, мы можем извлечь информацию о водяных метках из скриншотов документа. По сравнению с предыдущими алгоритмами нанесения водяных меток в документы, предлагаемая схема гарантирует независимое от контента встраивание, а также невидимость цифровой метки. Кроме того, предлагаемая схема маркирования показывает высокую точность извлечения.
Литература
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4. Rahman A.U., Sultan K., Musleh D., Aldhafferi N., Alqahtani A., Mahmud M. Robust and Fragile Medical Image Watermarking: A Joint Venture of Coding and Chaos Theories. Journal of Healthcare Engineering. 2018; 2018:8137436. (In Eng.) doi: https://doi.org/10.1155/2018/8137436
5. Tao H., Chongmin L., Zain J.M., Abdalla A.N. Robust Image Watermarking Theories and Techniques: A Review. Journal of Applied Research and Technology. 2014; 12(1):122-138. (In Eng.) doi: https://doi.org/10.1016/S1665-6423(14)71612-8
6. Anbarjafari G., Ozcinar C. Imperceptible non-blind watermarking and robustness against tone mapping operation attacks for high dynamic range images. Multimedia Tools and Applications. 2018; 77(18):24521-24535. (In Eng.) doi: https://doi.org/10.1007/s11042-018-5759-1
7. Pradhan C., Rath S., Bisoi A. Non Blind Digital Watermarking Technique Using DWT and Cross Chaos. Procedia Technology. 2012; 6:897-904. (In Eng.) doi: https://doi.org/10.1016/j.protcy.2012.10.109
8. Shahid A., et al. A Non-Blind Watermarking Scheme for Gray Scale Images in Discrete Wavelet Transform Domain using Two Subbands. International Journal of Computer Science Issues. 2012; 9(5-1):101-109. Available at: https://ijcsi.org/papers/IJCSI-9-5-1-101-109.pdf (accessed 23.12.2021). (In Eng.)
9. Memon N., Wong P.W. Protecting Digital Media Content. Communications of the ACM. 1998; 41(7):35-43. (In Eng.) doi: https://doi.org/10.1145/278476.278485
10. Kwok S.H., Yang C.C., Tam K.Y. Watermark design pattern for intellectual property protection in electronic commerce applications. Proceedings of the 33rd Annual Hawaii International Conference on System Sciences. IEEE Computer Society; 2000. p. 1-10. (In Eng.) doi: https://doi.org/10.1109/HICSS.2000.926859
11. Hartung F., Kutter M. Multimedia watermarking techniques. Proceedings of the IEEE. 1999; 87(7):1079-1107. (In Eng.) doi: https://doi.org/10.1109/5.771066
12. Topkara M., Taskiran C.M., Delp III E.J. Natural language watermarking. In: Delp III E.J., Wong P.W. Proceedings of SPIE: Security, Steganography, and Watermarking of Multimedia Contents VII. Vol. 5681. SPIE; 2005. p. 441-452. (In Eng.) doi: https://doi.org/10.1117/12.593790
13. Mali M.L., Patil N.N., Patil J.B. Implementation of Text Watermarking Technique Using Natural Language Watermarks. 2013 International Conference on Communication Systems and Network Technologies. IEEE Computer Society; 2013. p. 482-486. (In Eng.) doi: https://doi.org/10.1109/CSNT.2013.106
14. Jalil Z., Mirza A.M., Sabir M. Content based Zero-Watermarking Algorithm for Authentication of Text Documents. International Journal of Computer Science and Information Security. 2010; 7(2):212-217. (In Eng.)
15. Alotaibi R.A., Elrefaei L.A. Utilizing Word Space with Pointed and Un-pointed Letters for Arabic Text Watermarking. 2016 UKSim-AMSS 18th International Conference on Computer Modelling and Simulation (UKSim). IEEE Computer Society; 2016. p. 111-116. (In Eng.) doi: https://doi.org/10.1109/UKSim.2016.34
16. Sarkar T., Sanyal S. Digital Watermarking Techniques in Spatial and Frequency Domain. arXiv:1406.2146v2. 2014. (In Eng.) doi: https://doi.org/10.48550/arxiv.1406.2146
17. Saqib M., Naaz S. Spatial and Frequency Domain Digital Image Watermarking Techniques for Copyright Protection. International Journal of Engineering Science and Technology. 2017; 9(06):691-699. (In Eng.)
18. Bamatraf A., Ibrahim R., Salleh M.N.B.M. Digital watermarking algorithm using LSB. 2010 International Conference on Computer Applications and Industrial Electronics. IEEE Computer Society; 2010. p. 155-159. (In Eng.) doi: https://doi.org/10.1109/ICCAIE.2010.5735066
19. Dixit A., Dixit R. A Review on Digital Image Watermarking Techniques. International Journal of Image, Graphics and Signal Processing. 2017; 9(4):56-66. (In Eng.) doi: https://doi.org/10.5815/ijigsp.2017.04.07
20. Samcovic A., Turan J. Digital Image Watermarking by Spread Spectrum. Proceedings of the 11th Conference on 11th WSEAS International Conference on Communications ‒ Volume 11 (ICCOM'07). World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, Wisconsin, USA; 2007. p. 29-32. (In Eng.)
21. Hartung F.H., Su J.K., Girod B. Spread Spectrum Watermarking: Malicious Attacks and Counterattacks. Security and Watermarking of Multimedia Contents. Proceedings of SPIE: Security and Watermarking of Multimedia Contents. Vol. 3657. SPIE; 1999. p. 147-158. (In Eng.) doi: https://doi.org/10.1117/12.344665
22. Thanki R., Trivedi R., Kher R., Vyas D. Digital Watermarking Using White Gaussian Noise (WGN) in Spatial Domain. Proceeding of International Conference on Innovative Science and Engineering Technology (ICISET- 2011). Vol. 1. p. 38-42. (In Eng.)
23. Thanki R.M., Kher R.K., Vyas D.D. Robustness of Correlation Based Watermarking Techniques Using WGN against Different Order Statistics Filters. International Journal of Computer Science and Telecommunications. 2011; 2(4):45-49. Available at: https://www.ijcst.org/Volume2/Issue4/p9_2_4.pdf (accessed 23.12.2021). (In Eng.)
24. George L.E., Mohammed F.G., Taqi I.A. Effective Image Watermarking Method Based on DCT. Iraqi Journal of Science. 2015; 56(3B):2374-2379. Available at: https://www.iasj.net/iasj/download/ebbc3e942c16498f (accessed 23.12.2021). (In Eng.)
25. Pithiya P.M., Desai H.L. DCT Based Digital Image Watermarking, De- watermarking & Authentication. International Journal of Latest Trends in Engineering and Technology. 2013; 2(3):213-219. Available at: https://www.ijltet.org/pdfviewer.php?id=875&j_id=2633 (accessed 23.12.2021). (In Eng.)
26. Islam S. M. M., Debnath R., Hossain S. K. A. DWT Based Digital Watermarking Technique and its Robustness on Image Rotation, Scaling, JPEG compression, Cropping and Multiple Watermarking. 2007 International Conference on Information and Communication Technology. IEEE Computer Society; 2007. p. 246-249. (In Eng.) doi: https://doi.org/10.1109/ICICT.2007.375386
27. Savakar D.G., Pujar S. Digital Image Watermarking at Different Levels of DWT using RGB Channels. International Journal of Recent Technology and Engineering. 2020; 8(5):559-570. (In Eng.) doi: https://doi.org/10.35940/ijrte.D6821.018520
28. Liu R., Tan T. An SVD-based watermarking scheme for protecting rightful ownership. IEEE Transactions on Multimedia. 2002; 4(1):121-128. (In Eng.) doi: https://doi.org/10.1109/6046.985560
29. Jarušek R., Volna E., Kotyrba M. Neural Network Approach to Image Steganography Techniques. In: Matoušek R. (ed.) Mendel 2015. ICSC-MENDEL 2016. Advances in Intelligent Systems and Computing. Vol. 378. Springer, Cham; 2015. p. 317-327. (In Eng.) doi: https://doi.org/10.1007/978-3-319-19824-8_26
30. Tang W., Tan S., Li B., Huang J. Automatic Steganographic Distortion Learning Using a Generative Adversarial Network. IEEE Signal Processing Letters. 2017; 24(10):1547-1551. (In Eng.) doi: https://doi.org/10.1109/LSP.2017.2745572
31. Khan I., Verma B., Chaudhari V.K., Khan I. Neural network based steganography algorithm for still images. INTERACT-2010. IEEE Computer Society; 2010. p. 46-51. (In Eng.) doi: https://doi.org/10.1109/INTERACT.2010.5706192
32. Islam M., Roy A., Laskar R.H. SVM-based robust image watermarking technique in LWT domain using different sub-bands. Neural Computing and Applications. 2020; 32(5):1379-1403. (In Eng.) doi: https://doi.org/10.1007/s00521-018-3647-2
33. Yen C.-T., Huang Y.-J. Frequency domain digital watermark recognition using image code sequences with a back-propagation neural network. Multimedia Tools and Applications. 2016; 75(16):9745-9755. (In Eng.) doi: https://doi.org/10.1007/s11042-015-2718-y
34. Sun L., Xu J., Liu S., et al. A robust image watermarking scheme using Arnold transform and BP neural network. Neural Computing and Applications. 2018; 30(8):2425-2440. (In Eng.) doi: https://doi.org/10.1007/s00521-016-2788-4
35. Mun S.-M., Nam S.-H., Jang H., Kim D., Lee H.-K. Finding robust domain from attacks: A learning framework for blind watermarking. Neurocomputing. 2019; 337:191-202. (In Eng.) doi: https://doi.org/10.1016/j.neucom.2019.01.067
36. Pibre L., Pasquet J., Ienco D., Chaumont M. Deep learning is a good steganalysis tool when embedding key is reused for different images, even if there is a cover sourcemismatch. Proceeding IS&T Int’l. Symp. on Electronic Imaging: Media Watermarking, Security, and Forensics. Society for Imaging Science and Technology; 2016. (In Eng.) doi: https://doi.org/10.2352/ISSN.2470-1173.2016.8.MWSF-078
37. Doerr G., Dugelay J.-L. Collusion issue in video watermarking. Proceedings of SPIE: Security, Steganography, and Watermarking of Multimedia Contents VII. Vol. 5681. SPIE; 2005. p. 685-696. (In Eng.) doi: https://doi.org/10.1117/12.585783
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Опубликована
2022-03-31
Как цитировать
GURTOVA, Kristina Sergeevna.
Метод защиты информации цифровых документов с помощью невидимых цифровых меток и его реализация.
Современные информационные технологии и ИТ-образование, [S.l.], v. 18, n. 1, p. 152-166, mar. 2022.
ISSN 2411-1473. Доступно на: <http://sitito.cs.msu.ru/index.php/SITITO/article/view/841>. Дата доступа: 19 apr. 2024
doi: https://doi.org/10.25559/SITITO.18.202201.152-166.
Раздел
Исследования и разработки в области новых ИТ и их приложений
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