353 citations · 1.3k across the 38 of their papers we have counts for
5 papers · 1 filter
Set-Membership Inference Attacks using Data Watermarking
Mike Laszkiewicz, Denis Lukovnikov, Johannes Lederer +1
In this work, we propose a set-membership inference attack for generative models using deep image watermarking techniques. In particular, we demonstrate how conditional sampling fr…
Single-Model Attribution of Generative Models Through Final-Layer Inversion
Mike Laszkiewicz, Jonas Ricker, Johannes Lederer +1
Recent breakthroughs in generative modeling have sparked interest in practical single-model attribution. Such methods predict whether a sample was generated by a specific generator…
DistriBlock: Identifying adversarial audio samples by leveraging characteristics of the output distribution
Matías Pizarro, Dorothea Kolossa, Asja Fischer
Adversarial attacks can mislead automatic speech recognition (ASR) systems into predicting an arbitrary target text, thus posing a clear security threat. To prevent such attacks, w…
Uncertainty-based Detection of Adversarial Attacks in Semantic Segmentation
Kira Maag, Asja Fischer
State-of-the-art deep neural networks have proven to be highly powerful in a broad range of tasks, including semantic image segmentation. However, these networks are vulnerable aga…
Information Plane Analysis for Dropout Neural Networks
Linara Adilova, Bernhard C. Geiger, Asja Fischer
The information-theoretic framework promises to explain the predictive power of neural networks. In particular, the information plane analysis, which measures mutual information (M…