DeFake: Deploying a Tool for Robust Deepfake Detection

Collaborative Research: SaTC: TTP: Small: The objective of this transition-to-practice project is to “develop the DeFake tool, a system that utilizes advanced machine learning to help journalists detect deepfakes in a way that is robust, intuitive, and provides results that are explainable to the general public.

To meet this objective, the project team is engaged in four main tasks:
(1) Making the tool robust to new types of deepfakes, and having it show users why a video is fake;
(2) Protecting the tool from adversarial examples, e.g., small perturbations to a video that are specially crafted to fool detection systems;
(3) Working with journalists to understand what they need from the tool, and building an online community to discuss deepfakes and their detection; and
(4) Integrating advances from the other tasks into a stable, efficient, and useful tool, and actively disseminating this tool to journalists.

The project team is also leveraging visually interesting deepfakes to develop engaging education and outreach efforts, such as a museum-style exhibit on deepfake detection meant for broad audiences of all ages.”

About the award

October 1, 2021 - January 31, 2023

Project information

Academia

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