Document Open Access Logo

Media Forensics and the Challenge of Big Data (Dagstuhl Seminar 23021)

Authors Irene Amerini, Anderson Rocha, Paul L. Rosin, Xianfang Sun and all authors of the abstracts in this report

Thumbnail PDF


  • Filesize: 2.16 MB
  • 35 pages

Document Identifiers

Author Details

Irene Amerini
  • Sapienza University of Rome, IT
Anderson Rocha
  • State University - Campinas, BR
Paul L. Rosin
  • Cardiff University, GB
Xianfang Sun
  • Cardiff University, GB
and all authors of the abstracts in this report

Cite AsGet BibTex

Irene Amerini, Anderson Rocha, Paul L. Rosin, and Xianfang Sun. Media Forensics and the Challenge of Big Data (Dagstuhl Seminar 23021). In Dagstuhl Reports, Volume 13, Issue 1, pp. 1-35, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)


With demanding and sophisticated crimes and terrorist threats becoming more pervasive, allied with the advent and widespread of fake news, it becomes paramount to design and develop objective and scientific-based criteria to identify the characteristics of investigated materials associated with potential criminal activities. We need effective approaches to help us answer the four most important questions in forensics regarding an event: "who," "in what circumstances," "why," and "how." In recent years, the rise of social media has resulted in a flood of media content. As well as providing a challenge due to the increase in data that needs fact-checking, it also allows leveraging big-data techniques for forensic analysis. The seminar included sessions on traditional, deep learning-based methods, big data, benchmark and performance evaluation, applications, and future directions. It aimed to orchestrate the research community’s efforts in such a way that we harness different tools to fight misinformation and the spread of fake content.

Subject Classification

ACM Subject Classification
  • Applied computing → Computer forensics
  • Computing methodologies → Image manipulation
  • Digital forensics
  • Image and video authentication
  • Image and video forensics
  • Image and video forgery detection
  • Tampering detection


  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    PDF Downloads
Questions / Remarks / Feedback

Feedback for Dagstuhl Publishing

Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail