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DeepFakeChain

A Chain of Trust against Fake Multimedia Content

O ne of the latest challenges in the area of visual misinformation is the appearance of DeepFakes, i.e. AI-generated synthetic media using deep learning to create fake videos by swapping the face of a person with the face of another person. DeepFakeChain was funded by NGI TruBlo, an EU-funded project.

Although the scientific community is making progress in implementing tools that can help identify DeepFakes, we are still far from having methods that can automatically recognise any forgery. Even more challenging is the “arms race” nature of the problem, i.e. when new ways appear, new synthetic media may be generated that could circumvent them. To equip the fact-checking community with the necessary knowledge and resources to understand and counter the problem of DeepFakes, we propose the creation of a readily accessible web-based portal consisting of:

DeepFakeChain (DFC): a blockchain and related smart contracts for indexing content jointly identified as DeepFake by the required number of moderators, together with annotations that could help other users understand how it is possible to visually identify the forgeries in the cases that this is possible.
 
The DeepFake annotator: a tool that will allow authenticated users to annotate areas and/or time segments of candidate DeepFake material and which will enable other users either to confirm/reject its claims or even reuse these findings when working on other cases.
The search engine: an area where users can upload video or image content to check if visually similar material is already present in DFC.
 
The DeepFake checker: a service where users can submit video or image content to receive an automatic reply on the possibility of this being a DeepFake.
 

Zelus role and contribution:

Zelus worked with BlockChain capabilities to develop a content repository on cyber-attacks and response actions, empowered with blockchain-based security on attempts to compromise such content. Within DFCLab, Zelus aimed to expand its expertise with blockchain and distributed ledger technologies to support channel management, smart contract execution and moderators’ reputation scoring when checking and annotating multimedia online content for deepfakes