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A System for Mitigating the Problem of Deepfake News Videos Using Watermarking
Abstract
This paper describes how watermarking technology can be used to prevent the proliferation of Deepfake news. In the proposed system, digital watermarks are embedded in the audio and video tracks of video clips of trusted news agencies at the time the videos are captured or before they are distributed. The watermarks are detected at the social media network’s portals, nodes, and back ends. The embedded watermark imparts a unique identifier to the video, that links it to a blockchain. The watermarks also allow video source tracking, integrity verification, and alteration localization. The watermark detectors can be standalone software applications, or they can be integrated with other applications. They are used to perform three main tasks: (1) they alert the internet user when he watches an inauthentic news video, so that he may discard it, (2) they prevent a Deepfake news video from propagating through the network (3) they perform forensic analysis to help track and remove Deepfake news video postings. The paper includes Proof-of- Concept simulation results.
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Cited by
Qureshi, S. M., Saeed, A., Almotiri, S. H., Ahmad, F., & Al Ghamdi, M. A. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2037 · Cited by 71
Deepfakes: evolution and trends
Gil, R., Virgili‐Gomà, J., López, J. M., & García, R. (2023) · Soft Computing · doi:10.1007/s00500-023-08605-y · Cited by 46
Digital Watermarking—A Meta-Survey and Techniques for Fake News Detection
Malanowska, A., Mazurczyk, W., Araghi, T. K., Megías, D., & Kuribayashi, M. (2024) · IEEE Access · doi:10.1109/access.2024.3374201 · Cited by 33
Deepfake attack prevention using steganography GANs
Noreen, I., Muneer, M. S., & Gillani, S. A. (2022) · PeerJ Computer Science · doi:10.7717/peerj-cs.1125 · Cited by 27
Deepfakes in digital media forensics: Generation, AI-based detection and challenges
Bendiab, G., Haiouni, H., Moulas, I., & Shiaeles, S. N. (2024) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2024.103935 · Cited by 24
Metadata
- Authors
- Alattar, A., Sharma, R., & Scriven, J.
- ORCID
- Sharma, Ravi
- Venue
- Electronic Imaging
- Published
- 2020-01-26
- Volume
- 32
- Issue
- 4
- Pages
- 117-1-117-10
- ISSN
- 2470-1173 (ISSN-L)
- OpenAlex
- W3088210628
- Cited by
- 21
- References
- 0
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 7 · 2023: 5 · 2022: 2
- FWCI
- 0.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Electronic Imaging (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Steganography and Watermarking Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Keywords
- digital watermarking, video watermarking, blockchain, video integrity verification, misinformation mitigation, video forensics
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- CoChat. (2026). Citation check: A System for Mitigating the Problem of Deepfake News Videos Using Watermarking. https://app.cochat.ai/papers/10.2352/issn.2470-1173.2020.4.mwsf-117
- The paper
- Alattar, A., Sharma, R., & Scriven, J. (2020). A System for Mitigating the Problem of Deepfake News Videos Using Watermarking. Electronic Imaging. https://doi.org/10.2352/issn.2470-1173.2020.4.mwsf-117
