Про підвищення точності виявлення JPHIDE стеганограм: Fìz.-mat. model. ìnf. tehnol. 2021, 32:170-174
The paper proposes a method for improving the accuracy of steganoanalytical systems that use an ensemble classifier. The method involves a weighted final vote of several highly sensitive models of characteristic vectors. Its effectiveness was evaluated for the task of detecting steganograms created...
Збережено в:
| Дата: | 2021 |
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| Автор: | |
| Формат: | Стаття |
| Мова: | Українська |
| Опубліковано: |
Інститут прикладних проблем механіки і математики ім. Я. С. Підстригача НАН України
2021
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| Теми: | |
| Онлайн доступ: | https://www.fmmit.lviv.ua/index.php/fmmit/article/view/181 |
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| Назва журналу: | Physico-mathematical modeling and informational technologies |
Репозитарії
Physico-mathematical modeling and informational technologies| Резюме: | The paper proposes a method for improving the accuracy of steganoanalytical systems that use an ensemble classifier. The method involves a weighted final vote of several highly sensitive models of characteristic vectors. Its effectiveness was evaluated for the task of detecting steganograms created by the Jphide program. The accuracy obtained by usage of one of the models: LIU, CC-PEV, CC-C300, DCTR, PHARM, GFR and with using a combination of several models according to the developed method was compared. The test results proved that the weighted final voting of several highly sensitive models does increase the accuracy of the detection of steganograms with a relatively small payload (short secret messages) without compromising the accuracy of the detection of steganograms with a high payload.
References
Koshkina, N. V. (2020). Comparison of Efficiency of Statistical Models Used for Formation of Feature Vectors by JPEG Images Steganalysis. Theoretical and Applied Cybersecurity, 2(1), 22-28. DOI doi.org/10.20535/tacs.2664-29132020.1.209433
Koshkina, N. V. (2020). Research of Main Components of Machine Learning Based JPEG-Steganalysis Systems. Ukrainian Information Security Research Journal, 22(2), 97-108. http://jrnl.nau.edu.ua/index.php/ZI/article/view/14801/21490
Holub, V., Fridrich, J. (2015). Phase-Aware Projection Model for Steganalysis of JPEG Images, Proc. SPIE. Electronic Imaging, Media Watermarking, Security, and Forensics XVII. DOI doi.org/10.1117/12.2075239
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| DOI: | 10.15407/fmmit2021.32.170 |