Gradient Masking and the Underestimated Robustness Threats of Differential Privacy in Deep Learning

Franziska Boenisch, Philip Sperl, Konstantin Böttinger

An important problem in deep learning is the privacy and security of neural networks (NNs). Both aspects have long been considered separately. To date, it is still poorly understoo…