Learning and Sharing under Privacy constraints
About the project
The Learning and Sharing under Privacy constraints (DataLEASH) project will develop and test methods for more open data. In practice, it will consist of risk analysis for privacy protection (key indicators, methodology, legal requirements) and privacy configured learning systems (mechanisms, considerations of integrity and user value). It will support public organizations that are required to have open data and therefore need managing methods that are fast, reliable and uncomplicated. Based on these methods they are able to make well-informed decisions on how and if data should be shared (limiting access and various security settings) and choose what form of data conversion that should be aligned with a certain level of privacy and use.
Background
Privacy and managing sensitive data is a major challenge and growing with the increasing collections of data and advanced systems based on machine learning for public services. Legal restrictions e.g GDPR has improved privacy for managing personal data but there are still no guidelines for how to restrict data leakage and this has implications for how data can be shared and used.
Cross-disciplinary collaboration
DataLEASH brings together researchers from the School of Electrical Engineering and Computer Science (EECS, KTH), the Department of Computer and Systems Sciences (DSV) and the Department of Law both at Stockholm University and from the Decisions, Network, and Analytics lab at RISE.
Contacts
Tobias Oechtering
Professor, Division of Information Science and Engineering, Director Digitalisation Platform at KTH, Member of the Governing Board, Working group Trust, Digital Futures fellow, PI of research project Learning and Sharing under Privacy constraints (DataLEASH), Digital Futures Faculty
+46 8 790 84 62oech@kth.se
Sonja Buchegger
Professor, Division of Theoretical and Computer Science at KTH, Working group Trust, Co-PI of research project Learning and Sharing under Privacy constraints (DataLEASH), Digital Futures Faculty
+46 8 790 62 89buc@kth.se
Uno Fors
Professor, Department of Computer and Systems Science at Stockholm University, Member of the Executive Committee, Associate Director, Diversity and Inclusion, Co-PI of research project Learning and Sharing under Privacy constraints (DataLEASH), Digital Futures Faculty
+46 8 674 74 79uno@dsv.su.se
Cecilia Magnusson Sjöberg
Professor, LL.D., Department of Law at Stockholm University, Strategic Research Committee, Co-PI of research project Learning and Sharing under Privacy constraints (DataLEASH), Digital Futures Faculty
+46 8 162 893Cecilia.MagnussonSjoberg@juridicum.su.se
Sepideh Pashami
Senior Researcher at Data Analysis Unit, Digital Systems Division at RISE, Co-PI of research project Learning and Sharing under Privacy constraints (DataLEASH) at Digital Futures
+46 10 228 40 73sepideh.pashami@ri.se
Douglas Wikström
Associate Professor, Division of Theoretical Computer Science at KTH, Co-PI of research project Learning and Sharing under Privacy constraints (DataLEASH), Digital Futures Faculty
+46 8 790 81 38dog@kth.se