In the event of a pandemic, access to large-scale healthcare data is needed rapidly to investigate risk factors, treatment options and disease progression. However, the scientific community still lacks a secure infrastructure that enables international data sharing in a legally compliant and privacy-preserving manner. Modern cryptographic methods and approaches from the field of federated machine learning can provide solutions for this. The SCOR Consortium has developed a secure infrastructure that uses state-of-the-art data protection and security technologies to enable data sharing on a global scale while optimally protecting the privacy of the patients affected.
Further information can be found here and here.
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SCOR - An Initiative for Privacy-Preserving Global Research on COVID-19
The SCOR Consortium aims to use state-of-the-art cryptographic techniques to evaluate mass data on COVID-19, while protecting the privacy of patients.