research
∙
08/22/2023
Complex-valued neural networks for voice anti-spoofing
Current anti-spoofing and audio deepfake detection systems use either ma...
share
research
∙
02/08/2023
Shortcut Detection with Variational Autoencoders
For real-world applications of machine learning (ML), it is essential th...
research
∙
01/09/2023
Introducing Model Inversion Attacks on Automatic Speaker Recognition
Model inversion (MI) attacks allow to reconstruct average per-class repr...
research
∙
11/24/2022
Shortcut Removal for Improved OOD-Generalization
Machine learning is a data-driven discipline, and learning success is la...
research
∙
06/21/2022
R2-AD2: Detecting Anomalies by Analysing the Raw Gradient
Neural networks follow a gradient-based learning scheme, adapting their ...
research
∙
03/30/2022
Does Audio Deepfake Detection Generalize?
Current text-to-speech algorithms produce realistic fakes of human voice...
research
∙
02/01/2022
Visualizing Automatic Speech Recognition – Means for a Better Understanding?
Automatic speech recognition (ASR) is improving ever more at mimicking h...
research
∙
02/01/2022
Language Dependencies in Adversarial Attacks on Speech Recognition Systems
Automatic speech recognition (ASR) systems are ubiquitously present in o...
research
∙
07/20/2021
Human Perception of Audio Deepfakes
The recent emergence of deepfakes, computerized realistic multimedia fak...
research
∙
06/23/2021
Speech is Silver, Silence is Golden: What do ASVspoof-trained Models Really Learn?
We present our analysis of a significant data artifact in the official 2...
research
∙
05/17/2021
Gradient Masking and the Underestimated Robustness Threats of Differential Privacy in Deep Learning
An important problem in deep learning is the privacy and security of neu...
research
∙
04/14/2021
Defending against Adversarial Denial-of-Service Attacks
Data poisoning is one of the most relevant security threats against mach...
research
∙
02/12/2021
Deep Reinforcement Learning for Backup Strategies against Adversaries
Many defensive measures in cyber security are still dominated by heurist...
research
∙
01/26/2021
Adversarial Vulnerability of Active Transfer Learning
Two widely used techniques for training supervised machine learning mode...
research
∙
10/14/2020
Towards Resistant Audio Adversarial Examples
Adversarial examples tremendously threaten the availability and integrit...
research
∙
09/15/2020
Data Poisoning Attacks on Regression Learning and Corresponding Defenses
Adversarial data poisoning is an effective attack against machine learni...
research
∙
08/07/2020
Optimizing Information Loss Towards Robust Neural Networks
Neural Networks (NNs) are vulnerable to adversarial examples. Such input...
research
∙
03/03/2020
A^3: Activation Anomaly Analysis
Inspired by the recent advances in coverage-guided analysis of neural ne...
research
∙
11/05/2019
DLA: Dense-Layer-Analysis for Adversarial Example Detection
In recent years Deep Neural Networks (DNNs) have achieved remarkable res...
research
∙
08/14/2019
Side-Channel Aware Fuzzing
Software testing is becoming a critical part of the development cycle of...
research
∙
01/14/2018