دورية أكاديمية
Motion vector‐domain video steganalysis exploiting skipped macroblocks
| العنوان: | Motion vector‐domain video steganalysis exploiting skipped macroblocks |
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| المؤلفون: | Jun Li, Minqing Zhang, Ke Niu, Yingnan Zhang, Xiaoyuan Yang |
| المصدر: | IET Image Processing, Vol 18, Iss 5, Pp 1132-1144 (2024) |
| بيانات النشر: | Wiley, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Computer software |
| مصطلحات موضوعية: | digital forensics, steganography, video signal processing, Photography, TR1-1050, Computer software, QA76.75-76.765 |
| الوصف: | Abstract Video steganography has the potential to be used to convey illegal information, and video steganalysis is a vital tool to detect the presence of this illicit act. Currently, all the motion vector (MV)‐based video steganalysis algorithms extract feature sets directly from the MVs, but ignoring the embedding operation may perturb the statistical distribution of other video encoding elements, such as the skipped macroblocks (no direct MVs). This paper proposes a novel 11‐dimensional feature set to detect MV‐based video steganography based on the above observation. The proposed feature is extracted based on the skipped macroblocks by recompression calibration. Specifically, the feature consists of two components. The first is the probability distribution of motion vector prediction (MVP) difference, and the second is the probability distribution of partition state transfer. Extensive experiments on different conditions demonstrate that the proposed feature set achieves good detection accuracy, especially in lower embedding capacities. In addition, the loss of detection performance caused by recompression calibration using mismatched quantization parameters (QP) is within the acceptable range, so the proposed method can be used in practical scenarios. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1751-9667 1751-9659 |
| Relation: | https://doaj.org/toc/1751-9659; https://doaj.org/toc/1751-9667 |
| DOI: | 10.1049/ipr2.13014 |
| URL الوصول: | https://doaj.org/article/fd21757f3cc94701a9e56214dcc07b90 |
| رقم الأكسشن: | edsdoj.fd21757f3cc94701a9e56214dcc07b90 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 17519667 17519659 |
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| DOI: | 10.1049/ipr2.13014 |