Projet ANTIDOTE (Horizon Europe, appel à projets 2023)
Action : Staff Exchanges
Panel : Information Science and Engineering
Statut du projet : SIGNED

The smart healthcare domain utilizing a combination of Artificial Intelligence (AI) and medical Internet of Things devices is undoubtedly transforming the healthcare industry as it can deliver new applications and solutions that benefit patients, doctors and hospitals. Improved treatment, cost reduction and faster diagnosis are some of the advantages that smart healthcare brings to healthcare stakeholders. First, AI can be utilized to efficiently process data for improved disease diagnosis in medical images including liver lesion classification and segmentation, brain tumor segmentation, breast cancer detection, etc. Besides, AI can assist in securing the healthcare system from cybersecurity attacks that target the operation of medical IoT devices or sensitive medical data. However, the common assumption with AI is that the training, testing and deployment environment is benign and trustworthy. This assumption, however, does not hold true in general. As a matter of fact, research in this area has shown that small perturbations in the important features of AI models during training or testing phase can trivially undermine their performance. This gives rise to adversarial AI, in which attackers can trick healthcare AI models to degrade their diagnostic or cybersecurity detection performance. ANTIDOTE project objective is to create a sustainable European and inter-sectoral network of organizations working on a joint research programme in the interdisciplinary fields of Healthcare, AI and Cybersecurity. The participants will exchange skills and knowledge which will allow them to design and develop concrete mechanisms to evaluate the robustness of AI models and propose novel methods to ensure their secure, safe, resilient and robust operations in the healthcare domain. The outcomes of the ANTIDOTE project will have a significant benefit for European society, while strengthening the collaborative research between the different countries and sectors.

Mots clés : cybersecurity, medical image analysis, artificial intelligence, medical iot, adversarial ai, robust ai, cyberattack detection

Participants :
- National Inter-University Consortium for Telecommunications (Italie) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 184000.0 €
- Université Politehnica de Bucarest (Roumanie) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 174800.0 €
- Université Lusófona (Portugal) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 147200.0 €
- Infolysis p.c. (Grèce) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 165600.0 €
- Université ionienne (Grèce) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 266800.0 €
- Projecto Desenvolvimento Manutenção Formação e Consultadoria (Portugal) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 156400.0 €
- Université du Pirée (Grèce) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 257600.0 €
- Istrazivacko razvojni centar za bioinzenjering bioirc doo (Serbie) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 128800.0 €
- Université de Kragujevac (Serbie) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 119600.0 €