DP-UTIL: Comprehensive Utility Analysis of Differential Privacy in Machine Learning
Differential Privacy (DP) has emerged as a rigorous formalism to reason about quantifiable privacy leakage. In machine learning (ML), DP has been employed to limit …
PRICURE: Privacy-Preserving Collaborative Inference in a Multi-Party Setting
When multiple parties that deal with private data aim for a collaborative prediction task such as medical image classification, they are often constrained by data protection …