Ricerc@Sapienza

Disruptive technologies like Machine Learning (ML), cloud computing and big-data analytics will be largely adopted soon in healthcare, enabling personalized treatments, robotized surgeries, automatically generated diagnoses. Moreover, big data analytics and artificial intelligence could drive the discovery of new treatment.

The threat of cyber-attack on the healthcare applications is more and more serious over the last years. Malware, hijacking, social engineering, denial of service attacks, device tampering and physical thefts have been listed as the most serious threats to medical systems and applications. In the last two years, more than 100 million records were breached from the healthcare databases and more than 70000 machines infected by WannaCry Ransomware, including not only PCs, but also more specialist equipment such as MRI scanners or blood-storage refrigerators. Moreover, ML-based healthcare applications are sensible to specialized cyber-attacks, called adversarial attacks, difficult to detect; the privacy of patients could be posed at risk by data analytics on health records but also on genomics.

This project, hereafter PRISMA (PRIvacy-preserving, Security, and MAchine-learning techniques for healthcare applications) focuses on reducing cyber risks in healthcare by protecting healthcare applications from cyber-attacks and by preserving the privacy of patients' medical data. PRISMA foresees the collaboration of researchers in computer science and medicine (member of Stitch research center) with the goal of producing solutions that could be effectively applied in the healthcare sector. Specifically, PRISMA's objectives are:
- To develop a tool for the detection of adversarial attacks to ML-based healthcare applications
- To develop new techniques to preserve the privacy of medical data when processed by data analytics applications, and by ML-based applications.
- To develop advanced techniques to respond to cyber-attacks to healthcare applications.