Deepfake Media Forensics: Status and Future Challenges
The rise of AI-generated synthetic media, or deepfakes, has introduced unprecedented opportunities and challenges across various fields, including entertainment, cybersecurity, and digital communication. Using advanced frameworks such as Generative Adversarial Networks (GANs) and Diffusion Models (DMs), deepfakes are capable of producing highly realistic yet fabricated content, while these advancements enable creative and innovative applications, they also pose severe ethical, social, and security risks due to their potential misuse. The proliferation of deepfakes has triggered phenomena like "Impostor Bias", a growing skepticism toward the authenticity of multimedia content, further complicating trust in digital interactions. This paper is mainly based on the description of a research project called FF4ALL (FF4ALL-Detection of Deep Fake Media and Life-Long Media Authentication) for the detection and authentication of deepfakes, focusing on areas such as forensic attribution, passive and active authentication, and detection in real-world scenarios. By exploring both the strengths and limitations of current methodologies, we highlight critical research gaps and propose directions for future advancements to ensure media integrity and trustworthiness in an era increasingly dominated by synthetic media.
Authors
- Vittoria Bruni (ORCID: https://orcid.org/0000-0003-3909-7463)
- Pericle Perazzo (ORCID: https://orcid.org/0000-0003-3443-319X)
- Gian Luca Marcialis (ORCID: https://orcid.org/0000-0002-8719-9643)
- Stefano Tubaro (ORCID: https://orcid.org/0000-0002-1990-9869)
- Mauro Barni (ORCID: https://orcid.org/0000-0002-7368-0866)
- Marco Micheletto (ORCID: https://orcid.org/0000-0003-1196-7869)
- Nischay Purnekar (ORCID: https://orcid.org/0000-0003-1734-7476)
- Rocco De Nicola (ORCID: https://orcid.org/0000-0003-4691-7570)
- Taiba Majid Wani (ORCID: https://orcid.org/0000-0002-2335-0420)
- Giulia Boato (ORCID: https://orcid.org/0000-0002-0260-9528)
- Irene Amerini (ORCID: https://orcid.org/0000-0002-6461-1391)
- Davide Salvi (ORCID: https://orcid.org/0000-0002-5163-3364)
- Roberto Caldelli (ORCID: https://orcid.org/0000-0003-3471-1196)
- Massimo Villari (ORCID: https://orcid.org/0000-0001-9457-0677)
- Sebastiano Battiato (ORCID: https://orcid.org/0000-0001-6127-2470)
- Sara Mandelli (ORCID: https://orcid.org/0000-0003-3811-003X)
- Giovanni Puglisi (ORCID: https://orcid.org/0000-0001-6222-9933)
- Giulia Orrù (ORCID: https://orcid.org/0000-0002-7802-2483)
- Paolo Bestagini (ORCID: https://orcid.org/0000-0003-0406-0222)
- Luca Guarnera (ORCID: https://orcid.org/0000-0001-8315-351X)
- Andrea Montibeller (ORCID: https://orcid.org/0000-0002-0794-312X)
- Francesco G. B. De Natale (ORCID: https://orcid.org/0000-0003-2566-6995)
- Alessandro Ortis (ORCID: https://orcid.org/0000-0003-3461-4679)
- Domenico Vitulano (ORCID: https://orcid.org/0000-0001-6088-9743)
Institutions
- University of Siena (IT)
- University of Pisa (IT)
- University of Messina (IT)
- IMT School for Advanced Studies Lucca (IT)
- University of Cagliari (IT)
- University of Trento (IT)
- University of Catania (IT)
- Consorzio Nazionale Interuniversitario per le Telecomunicazioni (IT)
- Mercatorum University (IT)
- Sapienza University of Rome (IT)
- Politecnico di Milano (IT)
Publication Details
- Journal
- Journal of Imaging
- Published
- 2025-02-28
- DOI
- https://doi.org/10.3390/jimaging11030073
- Citations
- 55
- Primary Topic
- Digital Media Forensic Detection
- Type
- article
- Field-Weighted Citation Impact
- 70.18