Digital Watermarking—A Meta-Survey and Techniques for Fake News Detection
During the past few decades, research on digital media watermarking–initially designed for digital images with the envisioned applications of copyright protection or copy control– has significantly evolved with respect to other covers (i.e., video, audio, speech) and many more potential applications...
| Authors: | , , , , |
|---|---|
| Format: | article |
| Status: | Published version |
| Publication Date: | 2024 |
| Country: | España |
| Institution: | Universitat Oberta de Catalunya (UOC) |
| Repository: | O2, repositorio institucional de la UOC |
| OAI Identifier: | oai:openaccess.uoc.edu:10609/150410 |
| Online Access: | http://hdl.handle.net/10609/150410 http://doi.org/10.1109/ACCESS.2024.3374201 |
| Access Level: | Open access |
| Keyword: | digital watermarking fake news detection information hiding meta-survey signal processing |
| Summary: | During the past few decades, research on digital media watermarking–initially designed for digital images with the envisioned applications of copyright protection or copy control– has significantly evolved with respect to other covers (i.e., video, audio, speech) and many more potential applications, including tamper detection, broadcast monitoring, and, more recently, fake news detection. As a result, various surveys have tried to summarize certain aspects of this research field as it has grown. This has led to more than 130 survey papers being written at different points in time, describing various parts of the scientific efforts focused on digital media watermarking. Considering the above, the aim of this paper is twofold. First, we conduct a meta-survey based on 64 selected research works, in order to summarize the most notable survey papers in this field, which allows us to “draw a map” of this research area. Second, we focus on providing the requirements for digital watermarking techniques when applied to their most recent application: detecting fake news in multimedia content. Finally, an outline of the approach taken within the DISSIMILAR (Detection of fake newS on SocIal MedIa pLAtfoRms) project for the detection of disinformation is presented. |
|---|