Academy of Finland  
 
 
 
 
 
Funding decision
 
Organisation University of Helsinki
Project title Privacy Preserving Machine Learning over Partitioned Data
Applicant / Contact person Tajeddine, Razane
Decision No. 343555
Decision date 03.06.2021
Funding period 01.09.2021 - 31.08.2024
Funding 244 120
   
Project description
This project will be concerned with using machine learning techniques privately. In many cases, the datasets used for machine learning contain sensitive or confidential information. It is observed that the commonly used machine learning methods leak this sensitive information, which limits the usage of those methods. This gave rise to the field of privacy preserving machine learning. In this work, we will be concerned with private machine learning on data distributed to multiple parties, such that each party possesses a subset of the data. This project will result in software which will be publicly available and will give third parties the ability to use the data without having to access the confidential information. This builds trust in machine learning methods since no confidential data is publicly released, and consequently, allows for bigger datasets and better training models.