TY - GEN
T1 - (DFF '25) 1st Deepfake Forensics Workshop
T2 - 33rd ACM International Conference on Multimedia, MM 2025
AU - Battiato, Sebastiano
AU - Casu, Mirko
AU - Guarnera, Francesco
AU - Guarnera, Luca
AU - Puglisi, Giovanni
AU - Pontorno, Orazio
AU - Ragaglia, Claudio Vittorio
AU - Akhtar, Zahid
N1 - Publisher Copyright: © 2025 Owner/Author.
PY - 2025/10/27
Y1 - 2025/10/27
N2 - 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/
AB - 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/
KW - adversarial attacks
KW - deepfake attribution
KW - deepfake detection
KW - digital forensics
KW - generative models
UR - https://www.scopus.com/pages/publications/105024073170
U2 - 10.1145/3746027.3762241
DO - 10.1145/3746027.3762241
M3 - Conference contribution
T3 - MM 2025 - Proceedings of the 33rd ACM International Conference on Multimedia, Co-Located with MM 2025
SP - 14317
EP - 14319
BT - MM 2025 - Proceedings of the 33rd ACM International Conference on Multimedia, Co-Located with MM 2025
PB - Association for Computing Machinery, Inc
Y2 - 27 October 2025 through 31 October 2025
ER -