A Mechanism Design for Privacy-Preserving Computation on Shared Data

In times of surveillance and data retention, sharing information often comes together with privacy concerns. However, information sharing has benefits, e.g. sharing log files for including the knowledge gained from a broader view for security analysis, or sharing healthcare data for the use in studies for improving medical treatments. We present an information sharing framework design that meets both privacy and utility requirements of the information sharing parties. We utilize homomorphic encryption and show how it can be used for offline data analysis.