Privacy-Preserving Machine Learning: Threats and Solutions
Mohammad Al-Rubaie, J. Morris Chang · IEEE Security & Privacy · 2019
For privacy concerns to be addressed adequately in today's machine-learning (ML) systems, the knowledge gap between the ML and privacy communities must be bridged. This article aims to provide an introduction to the intersection of both fields with special emphasis on the techniques used to protect the data.