With the widespread diffusion of powerful media editing tools, falsifying images and videos has become easier and easier in the last few years. Fake multimedia, often used to support fake news, represents a growing menace in many fields of life, notably in politics, journalism, and the judiciary. In response to this threat, the signal processing community has produced a major research effort. A large number of methods have been proposed for source identification, forgery detection and localization, relying on the typical signal processing tools.
The advent of deep learning, however, is changing the rules of the game. On one hand, new sophisticated methods have been proposed to accomplish manipulations that were previously unthinkable, known as DeepFakes. On the other hand, deep learning provides also the analyst with new powerful forensic tools.
In this talk the most promising solutions for deepfakes detection will be presented with special attention to
methods that can be applied in realistic scenarios, such as when manipulated images and videos are spread out over social networks.
Luisa Verdoliva is Associate Professor at University Federico II of Naples. She has been Visiting Professor at Friedrich-Alexander-University in Erlangen and Visiting Scientist at Google AI in San Francisco.
She is the Principal Investigator for the Research Unit of University Federico II of Naples in the DISPARITY (Digital, Semantic and Physical Analysis of Media Integrity) project funded by DARPA under the MEDIFOR program. She is Associate Editor for IEEE Transactions on Information Forensics and Security and has been elected vice-chair of the IEEE Information Forensics and Security Technical Committee. In 2019 she was General co-Chair of the ACM Workshop on Information Hiding and Multimedia Security and Technical Program Chair of the IEEE Workshop in Information Forensics and Security. She led her research group in several international contests, including the recent 2018 IEEE Signal Processing Cup on camera model identification (first prize) and the 2013 IEEE Image Forensics Challenge (first prize both in the detection and localization tasks). Last year she received a Google Faculty Research Award.