AI4HEALTHSEC

A Dynamic and Self-Organized Artificial Swarm Intelligence Solution for Security and Privacy Threats in Healthcare ICT Infrastructures

Huge amounts of health data are generated every day. From test results to treatment decisions, records from digital devices such as pacemakers, lists of patients on wards and their ailments, and diagnoses and medication side effects. Our personal health data can have incredible applications for public health policy making and medical research.

But the value of this data also makes it extremely vulnerable to being targeted by hackers. Attacks are becoming more sophisticated as the value of such data increases. While paper records may be less efficient, digital records can be harder to store safely.

This project, funded by the European Union and run in collaboration between fifteen institutions and organisations, aims to use artificial intelligence to improve the security of Health Care Information Infrastructures (HCIIs).

Our project will deliver an Artificial Intelligence Dynamic Situational Awareness Framework (DSAF) that is able to:

• Improve, intensify and coordinate the overall security efforts for the effective and efficient identification, evaluation, investigation and mitigation of realistic risks, threats and multi-dimensional attacks within the cyber assets.
• Support, prepare and help the Interdependent HCIIs participating in different types of Health Care Supply Chain Services.

The DSAF itself will support:

• The Health Care Information Infrastructures (HCIIs) and the other stakeholders comprising the Health Care ecosystem to recognize, identify, model, and dynamically analyse cyber risks.
• Forecasting, treatment and response to advanced persistent threats and handle daily cyber-security and privacy risks, incidents and data breaches.

Scientists from the Institute for Analytics and Data Science (IADS) will bring to the project expertise in the areas of artificial intelligence, information security and privacy risk management. 

Funding

This project is funded by the European Union Horizon 2020 programme (Grant Agreement 883273).

Partners

This project is run with the following partners:

• Institute For High Performance Computing And Networking (Cnr) - Italy
• Aegis It Research Gmbh (Aegis) -  Germany
• EBIT S.R.L. (EBIT) - Italy
• Focal Point (Fp) - Belgium
• Fraunhofer Institute For Biomedical Engineering (FHG-IBMT) - Germany
• Idryma Technologias Kai Erevnas (Forth) - Greece
• Institute Of Communication And Computer Systems (ICCS) - Greece
• Klinikum Nurnberg (Klinik) - Germany
• Pdm E Fc Projecto Desenvolvi-Mento Manutencao Formacao E Consultadorialda (PDMFC) - Portugal
• Philips Electronics Nederland Bv (Philips) - Netherlands
• Privanova Sas (PN) - France
• Sphynx Technology Solutions Ag (STS) - Cyprus
• Tuv Trust It Gmbh-Unternehmen Sgruppe Tuv Austria (TUV) - Austria
• University Of Brighton (UoB) - UK
• University Of Essex (UoE) – UK