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Deepfake detection and Explainability using FOundation Representation Models

Objective

DEFORM addresses the urgent need for robust, explainable AI forensic tools to counter the growing threat of Deepfakes, AI-generated or manipulated audio, video, and images that challenge current forensic tools. The project will deliver a modular, practitioner-driven AI framework with multi-level explainability for multimodal Deepfake detection and source tracing, validated (TRL5) and demonstrated (TRL6) in 2 operational forensic environments. DEFORM’s innovative approach leverages emerging Foundation Representation Models and few-shot learning for robust and multi-level explainable AI (xAI) to ensure adaptability to new manipulation techniques and transparency for diverse stakeholders, including investigators, forensic examiners, legal professionals, and lay audiences.

The consortium unites leading scientific, technical, legal, and practitioner partners from six European countries, including police authorities and forensic institutes, to co-design, validate, and demonstrate solutions aligned with EU legal, ethical, and forensic standards. By twinning expert research partners in scientific, legal and ethical part from partner countries with practitioners from respective countries, DEFORM outputs include validated detection and source tracing modules for image, audio, and video; human-centred xAI explanations; annotated Deepfake datasets; and open-source forensic tools for wide adoption.

DEFORM’s impact pathway ensures improved reliability and usability for modern forensic analysis using new and emerging technology. This will enhance the capacity for law enforcement to fight against crimes in digital area and strengthen public trust. DEFORM's innovative training curricula will bridge the gap between research and operational practice. Also, stakeholder engagement will foster wide adoption and contribute to a strong and independent EU AI continent.

Fields of science (EuroSciVoc)

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Keywords

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Programme(s)

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Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-CL3-2025-01

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Coordinator

NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 392 875,00
Address
HOGSKOLERINGEN 1
7491 Trondheim
Norway

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Region
Norge Trøndelag Trøndelag
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 392 875,00

Participants (13)