Robust steganography with boundary-preserving overflow alleviation and adaptive error correction
With the rapid evolution of the Internet, the vast amount of data has created opportunities for fostering the development of steganographic techniques. However, traditional steganography faces challenges in social networks due to lossy operations such as spatial truncation during JPEG recompression,...
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| Vydáno v: | Expert systems with applications Ročník 281; s. 127598 |
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| Hlavní autoři: | , , |
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| Jazyk: | angličtina |
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Elsevier Ltd
01.07.2025
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| ISSN: | 0957-4174 |
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| Abstract | With the rapid evolution of the Internet, the vast amount of data has created opportunities for fostering the development of steganographic techniques. However, traditional steganography faces challenges in social networks due to lossy operations such as spatial truncation during JPEG recompression, with limited research on their effects. Existing methods aim to ensure the stability of the quantized coefficients by reducing the effects of spatial truncation. Nevertheless, these approaches may induce notable alterations to image pixels, potentially compromising anti-steganalysis performance. In this study, we analyze the overflow characteristics of spatial blocks and observe that pixel values at the boundaries of spatial blocks are more prone to overflow. Based on this observation, we propose a preprocessing method that performs overflow removal operations according to the actual overflow conditions of spatial blocks, enhancing coefficient stability while minimizing modifications to spatial block boundaries, thereby ensuring image quality. Subsequently, we employ adaptive error correction coding to reduce coding redundancy, thereby augmenting robustness and mitigating its impact on anti-steganalysis performance. The experimental results indicate that the proposed method possesses a strong embedding capacity, maintaining a high level of robustness while enhancing security.
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•Spatial block boundaries are more prone to overflow in JPEG recompression.•Preprocessing minimizes block modifications, enhancing stability and performance.•Adaptive error correction promptly saves the optimal scheme to enhance performance.•Method demonstrates significant advantages in anti-steganalysis performance. |
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| AbstractList | With the rapid evolution of the Internet, the vast amount of data has created opportunities for fostering the development of steganographic techniques. However, traditional steganography faces challenges in social networks due to lossy operations such as spatial truncation during JPEG recompression, with limited research on their effects. Existing methods aim to ensure the stability of the quantized coefficients by reducing the effects of spatial truncation. Nevertheless, these approaches may induce notable alterations to image pixels, potentially compromising anti-steganalysis performance. In this study, we analyze the overflow characteristics of spatial blocks and observe that pixel values at the boundaries of spatial blocks are more prone to overflow. Based on this observation, we propose a preprocessing method that performs overflow removal operations according to the actual overflow conditions of spatial blocks, enhancing coefficient stability while minimizing modifications to spatial block boundaries, thereby ensuring image quality. Subsequently, we employ adaptive error correction coding to reduce coding redundancy, thereby augmenting robustness and mitigating its impact on anti-steganalysis performance. The experimental results indicate that the proposed method possesses a strong embedding capacity, maintaining a high level of robustness while enhancing security.
[Display omitted]
•Spatial block boundaries are more prone to overflow in JPEG recompression.•Preprocessing minimizes block modifications, enhancing stability and performance.•Adaptive error correction promptly saves the optimal scheme to enhance performance.•Method demonstrates significant advantages in anti-steganalysis performance. |
| ArticleNumber | 127598 |
| Author | Cheng, Yu Yin, Zhaoxia Luo, Zhenlin |
| Author_xml | – sequence: 1 givenname: Yu orcidid: 0009-0005-3128-5613 surname: Cheng fullname: Cheng, Yu email: 10212140443@stu.ecnu.edu.cn – sequence: 2 givenname: Zhenlin orcidid: 0009-0001-3596-8009 surname: Luo fullname: Luo, Zhenlin email: 10212140438@stu.ecnu.edu.cn – sequence: 3 givenname: Zhaoxia orcidid: 0000-0003-0387-4806 surname: Yin fullname: Yin, Zhaoxia email: zxyin@cee.ecnu.edu.cn |
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| Cites_doi | 10.1109/TCSVT.2018.2881118 10.1145/1597817.1597830 10.1016/j.eswa.2023.121955 10.1109/TSIPN.2021.3081373 10.1016/j.eswa.2024.124903 10.1109/TIFS.2011.2134094 10.1109/18.923725 10.1016/j.eswa.2010.04.071 10.1109/TIFS.2014.2364918 10.1016/j.eswa.2024.123420 10.1016/j.sigpro.2019.107343 10.1109/TIFS.2020.3029908 10.1186/1687-417X-2014-1 10.1016/j.eswa.2024.124574 10.1109/TCSVT.2019.2923980 10.1016/j.eswa.2024.123715 10.1109/TCSVT.2023.3250750 10.1016/j.eswa.2024.124338 10.1016/j.eswa.2024.124390 10.1016/j.patrec.2005.09.008 10.1109/TMM.2023.3264628 10.1109/TIFS.2018.2885438 10.1007/s11042-017-4506-3 10.1016/j.jvcir.2024.104291 10.1016/j.eswa.2023.120416 10.1016/j.eswa.2024.124796 10.1016/j.ins.2024.120225 10.1016/j.eswa.2024.123540 10.1109/TIFS.2011.2175919 10.1109/TIFS.2018.2871749 |
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| Keywords | Adaptive error correction Robust steganography Social networks Dither modulation Overflow |
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| SubjectTerms | Adaptive error correction Dither modulation Overflow Robust steganography Social networks |
| Title | Robust steganography with boundary-preserving overflow alleviation and adaptive error correction |
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