(DFF '25) 1st Deepfake Forensics Workshop: Detection, Attribution, Recognition, and Adversarial Challenges in the Era of AI-Generated Media
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Le résumé fourni par la source
The proliferation of generative models, particularly Generative Adversarial Networks (GANs) and Diffusion Models, has reshaped multimedia content creation. Alongside creative and commercial opportunities, they have introduced unprecedented risks through the production of highly realistic synthetic content, or deepfakes. These artifacts challenge visual and auditory trust, with major implications for media, security, politics, and law. This workshop provides a forum to examine deepfake technology from forensic, technical, legal, and social perspectives. It will bring together experts to advance robust and explainable detection methods, define benchmarking practices, and address ethical and regulatory frameworks. Topics include detection and attribution, adversarial countermeasures, multimodal analysis, model traceability, legal admissibility of synthetic content, as well as real-world deployment challenges and dataset creation. Further information about the workshop is available at https://iplab.dmi.unict.it/mfs/acm-dff-ws-2025/
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- (DFF '25) 1st Deepfake Forensics Workshop: Detection, Attribution, Recognition, and Adversarial Challenges in the Era of AI-Generated Media
- Date Crossref
- 27/10/2025
- Éditeur
- ACM
- Type
- proceedings-article
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