DEFORM

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; humancentred 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.