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
1. Hiary H., Ng K. Watermark: From Paper Texture to Digital Media. First International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (AXMEDIS'05). IEEE Computer Society, USA; 2005. 4 p. (In Eng.) doi: https://doi.org/10.1109/AXMEDIS.2005.50
2. Tsolis D., Nikolopoulos S., Drossos L., Sioutas S., Papatheodorou T. Applying robust multibit watermarks to digital images. Journal of Computational and Applied Mathematics. 2009; 227(1):213-220. (In Eng.) doi: https://doi.org/10.1016/j.cam.2008.07.035
3. Zhang X., Wang S., Zhang K. Multi-bit Watermarking Scheme Based on Addition of Orthogonal Sequences. In: Gorodetsky V., Popyack L., Skormin V. (eds.). Computer Network Security. MMM-ACNS 2003. Lecture Notes in Computer Science. Vol. 2776. Springer, Berlin, Heidelberg; 2003. p. 407-418. (In Eng.) doi: https://doi.org/10.1007/978-3-540-45215-7_35
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
38. Xie G., Shen H. Robust wavelet-based blind image watermarking against geometrical attacks. 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763). Vol. 3. IEEE Computer Society; 2004. p. 2051-2054. (In Eng.) doi: https://doi.org/10.1109/ICME.2004.1394668
39. Venturini I. Counteracting Oracle attacks. Proceedings of the 2004 workshop on Multimedia and security (MM&Sec'04). Association for Computing Machinery, New York, NY, USA; 2004. p. 187-192. (In Eng.) doi: https://doi.org/10.1145/1022431.1022464
40. Zhang X., Wang S. Invertibility attack against watermarking based on forged algorithm and a countermeasure. Pattern Recognition Letters. 2004; 25(8):967-973. (In Eng.) doi: https://doi.org/10.1016/j.patrec.2004.02.007
41. Kutter M., Voloshynovskiy S.V., Herrigel A. Watermark Copy Attack. Proceedings of SPIE: Security and Watermarking of Multimedia Contents II. Vol. 3971. SPIE; 2000. p. 371-380. (In Eng.) doi: https://doi.org/10.1117/12.384991
42. Srivatsan N., Barron J., Klein D., Berg-Kirkpatrick T. A Deep Factorization of Style and Structure in Fonts. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Hong Kong, China. Association for Computational Linguistics; 2019. p. 2195-2205. (In Eng.) doi: https://doi.org/10.18653/v1/D19-1225
43. Campbell N.D.F., Kautz J. Learning a manifold of fonts. ACM Transactions on Graphics. 2014; 33(4):91. (In Eng.) doi: https://doi.org/10.1145/2601097.2601212
44. Cu V.L., Burie J. -C., Ogier J. -M., Liu C. -L. Hiding Security Feature Into Text Content for Securing Documents Using Generated Font. 2019 International Conference on Document Analysis and Recognition (ICDAR). IEEE Computer Society; 2019. p. 1214-1219. (In Eng.) doi: https://doi.org/10.1109/ICDAR.2019.00196
45. Zramdini A., Ingold R. Optical font recognition using typographical features. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1998; 20(8):877-882. (In Eng.) doi: https://doi.org/10.1109/34.709616
46. Peterson W.W., Brown D.T. Cyclic Codes for Error Detection. Proceedings of the IRE. 1961; 49(1):228-235. (In Eng.) doi: https://doi.org/10.1109/ JRPROC.1961.287814
47. Bose R.C., Ray-Chaudhuri D.K. On a class of error correcting binary group codes. Information and Control. 1960; 3(1):68-79. (In Eng.) doi: https://doi.org/10.1016/S0019-9958(60)90287-4
48. Smith R. An Overview of the Tesseract OCR Engine. Ninth International Conference on Document Analysis and Recognition (ICDAR 2007). Vol. 2. IEEE Computer Society; 2007. p. 629-633. (In Eng.) doi: https://doi.org/10.1109/ICDAR.2007.4376991
49. Wang Z., Bovik A.C., Sheikh H.R., Simoncelli E.P. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing. 2004; 13(4):600-612. (In Eng.) doi: https://doi.org/10.1109/TIP.2003.819861
50. Chen G., et al. Large-Scale Visual Font Recognition. 2014 IEEE Conference on Computer Vision and Pattern Recognition. IEEE Computer Society; 2014. p. 3598-3605. (In Eng.) doi: https://doi.org/10.1109/CVPR.2014.460
51. Kingma D.P., Ba J.L. Adam: A Method for Stochastic Optimization. arXiv:1412.6980v9. 2014. (In Eng.) doi: https://doi.org/10.48550/arxiv.1412.6980
52. Canziani A., Paszke A., Culurciello E. An Analysis of Deep Neural Network Models for Practical Applications. arXiv:1605.07678v4. 2016. (In Eng.) doi: https://doi.org/10.48550/arXiv.1605.07678
2. Tsolis D., Nikolopoulos S., Drossos L., Sioutas S., Papatheodorou T. Applying robust multibit watermarks to digital images. Journal of Computational and Applied Mathematics. 2009; 227(1):213-220. (In Eng.) doi: https://doi.org/10.1016/j.cam.2008.07.035
3. Zhang X., Wang S., Zhang K. Multi-bit Watermarking Scheme Based on Addition of Orthogonal Sequences. In: Gorodetsky V., Popyack L., Skormin V. (eds.). Computer Network Security. MMM-ACNS 2003. Lecture Notes in Computer Science. Vol. 2776. Springer, Berlin, Heidelberg; 2003. p. 407-418. (In Eng.) doi: https://doi.org/10.1007/978-3-540-45215-7_35
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
38. Xie G., Shen H. Robust wavelet-based blind image watermarking against geometrical attacks. 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763). Vol. 3. IEEE Computer Society; 2004. p. 2051-2054. (In Eng.) doi: https://doi.org/10.1109/ICME.2004.1394668
39. Venturini I. Counteracting Oracle attacks. Proceedings of the 2004 workshop on Multimedia and security (MM&Sec'04). Association for Computing Machinery, New York, NY, USA; 2004. p. 187-192. (In Eng.) doi: https://doi.org/10.1145/1022431.1022464
40. Zhang X., Wang S. Invertibility attack against watermarking based on forged algorithm and a countermeasure. Pattern Recognition Letters. 2004; 25(8):967-973. (In Eng.) doi: https://doi.org/10.1016/j.patrec.2004.02.007
41. Kutter M., Voloshynovskiy S.V., Herrigel A. Watermark Copy Attack. Proceedings of SPIE: Security and Watermarking of Multimedia Contents II. Vol. 3971. SPIE; 2000. p. 371-380. (In Eng.) doi: https://doi.org/10.1117/12.384991
42. Srivatsan N., Barron J., Klein D., Berg-Kirkpatrick T. A Deep Factorization of Style and Structure in Fonts. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Hong Kong, China. Association for Computational Linguistics; 2019. p. 2195-2205. (In Eng.) doi: https://doi.org/10.18653/v1/D19-1225
43. Campbell N.D.F., Kautz J. Learning a manifold of fonts. ACM Transactions on Graphics. 2014; 33(4):91. (In Eng.) doi: https://doi.org/10.1145/2601097.2601212
44. Cu V.L., Burie J. -C., Ogier J. -M., Liu C. -L. Hiding Security Feature Into Text Content for Securing Documents Using Generated Font. 2019 International Conference on Document Analysis and Recognition (ICDAR). IEEE Computer Society; 2019. p. 1214-1219. (In Eng.) doi: https://doi.org/10.1109/ICDAR.2019.00196
45. Zramdini A., Ingold R. Optical font recognition using typographical features. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1998; 20(8):877-882. (In Eng.) doi: https://doi.org/10.1109/34.709616
46. Peterson W.W., Brown D.T. Cyclic Codes for Error Detection. Proceedings of the IRE. 1961; 49(1):228-235. (In Eng.) doi: https://doi.org/10.1109/ JRPROC.1961.287814
47. Bose R.C., Ray-Chaudhuri D.K. On a class of error correcting binary group codes. Information and Control. 1960; 3(1):68-79. (In Eng.) doi: https://doi.org/10.1016/S0019-9958(60)90287-4
48. Smith R. An Overview of the Tesseract OCR Engine. Ninth International Conference on Document Analysis and Recognition (ICDAR 2007). Vol. 2. IEEE Computer Society; 2007. p. 629-633. (In Eng.) doi: https://doi.org/10.1109/ICDAR.2007.4376991
49. Wang Z., Bovik A.C., Sheikh H.R., Simoncelli E.P. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing. 2004; 13(4):600-612. (In Eng.) doi: https://doi.org/10.1109/TIP.2003.819861
50. Chen G., et al. Large-Scale Visual Font Recognition. 2014 IEEE Conference on Computer Vision and Pattern Recognition. IEEE Computer Society; 2014. p. 3598-3605. (In Eng.) doi: https://doi.org/10.1109/CVPR.2014.460
51. Kingma D.P., Ba J.L. Adam: A Method for Stochastic Optimization. arXiv:1412.6980v9. 2014. (In Eng.) doi: https://doi.org/10.48550/arxiv.1412.6980
52. Canziani A., Paszke A., Culurciello E. An Analysis of Deep Neural Network Models for Practical Applications. arXiv:1605.07678v4. 2016. (In Eng.) doi: https://doi.org/10.48550/arXiv.1605.07678
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: 21 nov. 2024
doi: https://doi.org/10.25559/SITITO.18.202201.152-166.
Раздел
Исследования и разработки в области новых ИТ и их приложений
Это произведение доступно по лицензии Creative Commons «Attribution» («Атрибуция») 4.0 Всемирная.
Редакционная политика журнала основывается на традиционных этических принципах российской научной периодики и строится с учетом этических норм работы редакторов и издателей, закрепленных в Кодексе поведения и руководящих принципах наилучшей практики для редактора журнала (Code of Conduct and Best Practice Guidelines for Journal Editors) и Кодексе поведения для издателя журнала (Code of Conduct for Journal Publishers), разработанных Комитетом по публикационной этике - Committee on Publication Ethics (COPE). В процессе издательской деятельности редколлегия журнала руководствуется международными правилами охраны авторского права, нормами действующего законодательства РФ, международными издательскими стандартами и обязательной ссылке на первоисточник.
Журнал позволяет авторам сохранять авторское право без ограничений. Журнал позволяет авторам сохранить права на публикацию без ограничений.
Издательская политика в области авторского права и архивирования определяются «зеленым цветом» в базе данных SHERPA/RoMEO.
Все статьи распространяются на условиях лицензии Creative Commons «Attribution» («Атрибуция») 4.0 Всемирная, которая позволяет другим использовать, распространять, дополнять эту работу с обязательной ссылкой на оригинальную работу и публикацию в этом журналe.
