Mesh Discriminative Features for 3D Steganalysis
- Submitting institution
-
University of Durham
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 101598
- Type
- D - Journal article
- DOI
-
10.1145/2535555
- Title of journal
- ACM Transactions on Multimedia Computing, Communications, and Applications
- Article number
- 27
- First page
- -
- Volume
- 10
- Issue
- 3
- ISSN
- 15516857
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2014
- URL
-
https://doi.org/10.1145/2535555
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
-
B - Algorithms and Complexity
- Citation count
- 12
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The following papers use our approach as a baseline to validate their steganalytic algorithms: "Steganalysis of 3D Objects Using Statistics of Local Feature Sets" doi:10.1016/j.ins.2017.06.011, “Steganalysis of meshes based on 3D wavelet multiresolution analysis” doi: 10.1016/j.ins.2020.02.061. Our paper is included in the survey “Comprehensive survey of 3D image steganography techniques” doi:10.1049/iet-ipr.2017.0162. In the paper "An efficient 3D information hiding algorithm based on sampling concepts" doi: 10.1007/s11042-017-4483-6, the authors cite our paper in their concluding future work paragraph, mentioning that 3D steganalysis is a nascent area compared to the more developed 3D steganography.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -