[21-06-11] Scalable privacy-preserving technologies for crossborder federated computation in Europe involving personal data
The two tables below can be used when a European organization is looking for project partner, i.e. a specific type of organization, with a specific type of skill or interest.
The first table shows the skills and interests among a number of potential partners. When searching for a specific skill, start by looking at column 1. For each skill the potential partners are listed in the same row. The organization’s names are also links to their home pages.
The second table below shows all the organizations that are interested in this call, and also the types of organization (SME, startup, RTO etc.).
If you are interested in getting in touch with any of these organizations, please contact the node for more information at firstname.lastname@example.org.
|Type of expertise needed||Organisations|
|GDPR||Karlstads universitet, PICS/Högskolan i Skövde, Omen technologies, Göteborgs stad|
|Big Data||Göteborgs stad|
|Advanced privacy preserving computation|
techniques such as homomorphic encryption, secure
multiparty computation, and differential privacy
|Real-world use case scenarios||Linköpings universitet, Göteborgs stad, PICS/Högskolan i Skövde|
|Integration with existing infrastructures and traditional security measures||Linköpings universitet, Göteborgs stad|
|User’s needs||Defentry, PICS/Högskolan i Skövde, Göteborgs stad|
|Legacy variation in personal data types||Defentry, Göteborgs stad|
|Privacy-preserving computation in realistic federated data infrastructures||Karlstads universitet|
|EU health data space||Göteborgs stad|
|Developed as open source software||Defentry, PICS/Högskolan i Skövde|