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.
Media Forensics and the Challenge of Big Data (Dagstuhl Seminar 23021) / Amerini, Irene; Rocha, Anderson; Rosin, Paul L.; Sun, Xianfang. - In: DAGSTUHL REPORTS. - ISSN 2192-5283. - 13:1(2023), pp. 1-35. [10.4230/dagrep.13.1.1]
Media Forensics and the Challenge of Big Data (Dagstuhl Seminar 23021)
Irene Amerini
;
2023
Abstract
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.File | Dimensione | Formato | |
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Amerini_Media-Forensics _2023.pdf
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Note: https://doi.org/10.4230/DagRep.13.1.1
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