8 citations · 16 across the 2 of their papers we have counts for
2 papers
cs.SD2023★ 8 cited
Introducing Model Inversion Attacks on Automatic Speaker Recognition
Karla Pizzi, Franziska Boenisch, Ugur Sahin +1
Model inversion (MI) attacks allow to reconstruct average per-class representations of a machine learning (ML) model's training data. It has been shown that in scenarios where each…
cs.CR2021★ 8 cited
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…