Efficient Video Steganalytic Feature Design by Exploiting Local Optimality and Lagrangian Cost Quotient
As the opponent of motion vector (MV)-based video steganography, the corresponding symmetric steganalysis has also developed a lot in recent years, among which the logic-based steganalytic schemes, e.g., AoSO, NPELO and MVC, are the most prevailing. Although currently achieving the best detection pe...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Symmetry |
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| Online Access: | https://www.mdpi.com/2073-8994/15/2/520 |
| _version_ | 1797618042733068288 |
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| author | Ying Liu Jiangqun Ni Wenkang Su |
| author_facet | Ying Liu Jiangqun Ni Wenkang Su |
| author_sort | Ying Liu |
| collection | DOAJ |
| description | As the opponent of motion vector (MV)-based video steganography, the corresponding symmetric steganalysis has also developed a lot in recent years, among which the logic-based steganalytic schemes, e.g., AoSO, NPELO and MVC, are the most prevailing. Although currently achieving the best detection performance, these steganalytic schemes are less effective in detecting some logic-maintaining steganographic schemes. In view of the fact that the distributions of covers’ local Lagrangian cost quotients are normally more concentrated in the small value ranges than those of stegos and “spread” to the large values ranges after modifying the motion vector, the local Lagrangian cost quotient would thus be an efficient indicator to reflect the difference between cover videos and stego ones. In this regard, combining the logic-based (Lg) and local Lagrangian cost quotient (LLCQ)-based feature, we finally proposed a more effective and general steganalysis feature, i.e., Lg-LLCQ, which is composed of diverse subfeatures and performs much better than the corresponding single-type feature. Extensive experimental results show that the proposed method exhibits detection performance superior to other state-of-the-art schemes and even works well under cover sources and steganographic scheme mismatch scenes, which indicates our proposed feature is more conducive to real-world applications. |
| first_indexed | 2024-03-11T08:04:36Z |
| format | Article |
| id | doaj.art-27788b463c334e76919b68cd82ebd740 |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-11T08:04:36Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-27788b463c334e76919b68cd82ebd7402023-11-16T23:34:26ZengMDPI AGSymmetry2073-89942023-02-0115252010.3390/sym15020520Efficient Video Steganalytic Feature Design by Exploiting Local Optimality and Lagrangian Cost QuotientYing Liu0Jiangqun Ni1Wenkang Su2School of Electronics and Information Engineering, Sun Yat-sen University, Guangzhou 510006, ChinaSchool of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, ChinaSchool of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, ChinaAs the opponent of motion vector (MV)-based video steganography, the corresponding symmetric steganalysis has also developed a lot in recent years, among which the logic-based steganalytic schemes, e.g., AoSO, NPELO and MVC, are the most prevailing. Although currently achieving the best detection performance, these steganalytic schemes are less effective in detecting some logic-maintaining steganographic schemes. In view of the fact that the distributions of covers’ local Lagrangian cost quotients are normally more concentrated in the small value ranges than those of stegos and “spread” to the large values ranges after modifying the motion vector, the local Lagrangian cost quotient would thus be an efficient indicator to reflect the difference between cover videos and stego ones. In this regard, combining the logic-based (Lg) and local Lagrangian cost quotient (LLCQ)-based feature, we finally proposed a more effective and general steganalysis feature, i.e., Lg-LLCQ, which is composed of diverse subfeatures and performs much better than the corresponding single-type feature. Extensive experimental results show that the proposed method exhibits detection performance superior to other state-of-the-art schemes and even works well under cover sources and steganographic scheme mismatch scenes, which indicates our proposed feature is more conducive to real-world applications.https://www.mdpi.com/2073-8994/15/2/520video steganalysisvideo steganographymotion vectorlocal Lagrangian cost quotient |
| spellingShingle | Ying Liu Jiangqun Ni Wenkang Su Efficient Video Steganalytic Feature Design by Exploiting Local Optimality and Lagrangian Cost Quotient Symmetry video steganalysis video steganography motion vector local Lagrangian cost quotient |
| title | Efficient Video Steganalytic Feature Design by Exploiting Local Optimality and Lagrangian Cost Quotient |
| title_full | Efficient Video Steganalytic Feature Design by Exploiting Local Optimality and Lagrangian Cost Quotient |
| title_fullStr | Efficient Video Steganalytic Feature Design by Exploiting Local Optimality and Lagrangian Cost Quotient |
| title_full_unstemmed | Efficient Video Steganalytic Feature Design by Exploiting Local Optimality and Lagrangian Cost Quotient |
| title_short | Efficient Video Steganalytic Feature Design by Exploiting Local Optimality and Lagrangian Cost Quotient |
| title_sort | efficient video steganalytic feature design by exploiting local optimality and lagrangian cost quotient |
| topic | video steganalysis video steganography motion vector local Lagrangian cost quotient |
| url | https://www.mdpi.com/2073-8994/15/2/520 |
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