Privacy through Co-Design for Real-World Data Analytics in the Cloud
- Zsolt István(PI),
- Paul Rosero(CoI)
Project:
Research
Project status
Finished
Description
Key themes within call:
•Interdisciplinary research rooted in the natural and technical sciences
•Technology for tomorrow’s medical science and applications
Lay Project Description:
The project aims to drastically reduce the cost of data monitoring, tracking, and transformation operators used for enforcing privacy and data protection in analytics applications. This will be achieved through a co-design approach to re-imagine operators for tomorrow’s cloud hardware, including accelerators.
The project will bring innovation in the form of efficient “data protection infrastructure” for modern data analytics. Such analytics have been instrumental in numerous fields, including ones such as personalized medicine. This is one of our target use-cases since it is representative for analytics that combine data from different sources and are subject to strict regulations. Enforcement, however, often reduces the usefulness of data and slows down computation significantly. The project sets out to break this tradeoff.
Being funded will allow the experienced researcher to bootstrap his team at ITU faster and will pave the way for national collaborations and tech transfer. Students trained will acquire skills spanning traditional domain boundaries, placing them on impactful career paths.
•Interdisciplinary research rooted in the natural and technical sciences
•Technology for tomorrow’s medical science and applications
Lay Project Description:
The project aims to drastically reduce the cost of data monitoring, tracking, and transformation operators used for enforcing privacy and data protection in analytics applications. This will be achieved through a co-design approach to re-imagine operators for tomorrow’s cloud hardware, including accelerators.
The project will bring innovation in the form of efficient “data protection infrastructure” for modern data analytics. Such analytics have been instrumental in numerous fields, including ones such as personalized medicine. This is one of our target use-cases since it is representative for analytics that combine data from different sources and are subject to strict regulations. Enforcement, however, often reduces the usefulness of data and slows down computation significantly. The project sets out to break this tradeoff.
Being funded will allow the experienced researcher to bootstrap his team at ITU faster and will pave the way for national collaborations and tech transfer. Students trained will acquire skills spanning traditional domain boundaries, placing them on impactful career paths.
Project Information
Project Type
Research
Acronym
PRIVACOTime Period
01/01/2021 – 31/12/2022Status
FinishedID
External Project ID: NNF20OC0064411
Funding Details
PRIVACO - Privacy through Co-Design for Real-World Data Analytics in the CloudAward
FundersAmounts
Novo Nordisk Foundation
1050883 DKK