Distributed Anomaly Detection of Single Mote Attacks in RPL Networks. - Nicolas M. Müller; Pascal Debus; Daniel Kowatsch; Konstantin Böttinger (ICETE (2), 2019)

Identifying Mislabeled Instances in Classification Datasets. - Nicolas M. Müller; Karla Markert (IJCNN, 2019)

On GDPR Compliance of Companies' Privacy Policies. - Nicolas M. Müller; Daniel Kowatsch; Pascal Debus; Donika Mirdita; Konstantin Böttinger (TSD, 2019)

Data Poisoning Attacks on Regression Learning and Corresponding Defenses. - Nicolas M. Müller; Daniel Kowatsch; Konstantin Böttinger (PRDC, 2020)

Towards Resistant Audio Adversarial Examples. - Tom Dörr; Karla Markert; Nicolas M. Müller; Konstantin Böttinger (CoRR, 2020)

Adversarial Vulnerability of Active Transfer Learning. - Nicolas M. Müller; Konstantin Böttinger (IDA, 2021)

SC-GlowTTS: An Efficient Zero-Shot Multi-Speaker Text-To-Speech Model. - Edresson Casanova; Christopher Shulby; Eren Gölge; Nicolas Michael Müller; Frederico Santos de Oliveira; Arnaldo Candido Jr.; Anderson da Silva Soares; Sandra Maria Aluísio; Moacir Antonelli Ponti (Interspeech, 2021)

Deep Reinforcement Learning for Backup Strategies against Adversaries. - Pascal Debus; Nicolas M. Müller; Konstantin Böttinger (CoRR, 2021)

Defending against Adversarial Denial-of-Service Attacks. - Nicolas M. Müller; Simon Roschmann; Konstantin Böttinger (CoRR, 2021)

Speech is Silver, Silence is Golden: What do ASVspoof-trained Models Really Learn? - Nicolas M. Müller; Franziska Dieckmann; Pavel Czempin; Roman Canals; Konstantin Böttinger (CoRR, 2021)

Human Perception of Audio Deepfakes. - Nicolas M. Müller; Karla Markert; Konstantin Böttinger (CoRR, 2021)

Does Audio Deepfake Detection Generalize? - Nicolas M. Müller; Pavel Czempin; Franziska Dieckmann; Adam Froghyar; Konstantin Böttinger (INTERSPEECH, 2022)

Attacker Attribution of Audio Deepfakes. - Nicolas M. Müller; Franziska Dieckmann; Jennifer Williams 001 (INTERSPEECH, 2022)

Human Perception of Audio Deepfakes. - Nicolas M. Müller; Karla Pizzi; Jennifer Williams 001 (DDAM@MM, 2022)

Shortcut Removal for Improved OOD-Generalization. - Nicolas M. Müller; Jochen Jacobs; Jennifer Williams 001; Konstantin Böttinger (CoRR, 2022)

Protecting Publicly Available Data With Machine Learning Shortcuts. - Nicolas M. Müller; Maximilian Burgert; Pascal Debus; Jennifer Williams 001; Philip Sperl; Konstantin Böttinger (BMVC, 2023)

Localized Shortcut Removal. - Nicolas M. Müller; Jochen Jacobs; Jennifer Williams 001; Konstantin Böttinger (CVPR Workshops, 2023)

Complex-valued neural networks for voice anti-spoofing. - Nicolas M. Müller; Philip Sperl; Konstantin Böttinger (INTERSPEECH, 2023)

MLAAD: The Multi-Language Audio Anti-Spoofing Dataset. - Nicolas M. Müller; Piotr Kawa; Wei Herng Choong; Edresson Casanova; Eren Gölge; Thorsten Müller; Piotr Syga; Philip Sperl; Konstantin Böttinger (IJCNN, 2024)

Shortcut Detection With Variational Autoencoders. - Nicolas M. Müller; Simon Roschmann; Shahbaz Khan 009; Philip Sperl; Konstantin Böttinger (IJCNN, 2024)

Harder or Different? Understanding Generalization of Audio Deepfake Detection. - Nicolas M. Müller; Nicholas W. D. Evans; Hemlata Tak; Philip Sperl; Konstantin Böttinger (INTERSPEECH, 2024)

A New Approach to Voice Authenticity. - Nicolas M. Müller; Piotr Kawa; Shen Hu; Matthias Neu; Jennifer Williams 001; Philip Sperl; Konstantin Böttinger (INTERSPEECH, 2024)

Imbalance in Regression Datasets. - Daniel Kowatsch; Nicolas M. Müller; Kilian Tscharke; Philip Sperl; Konstantin Böttinger (CoRR, 2024)

Easy, Interpretable, Effective: openSMILE for voice deepfake detection. - Octavian Pascu; Dan Oneata; Horia Cucu; Nicolas M. Müller (ICASSP, 2025)

DeePen: Penetration Testing for Audio Deepfake Detection. - Nicolas M. Müller; Piotr Kawa; Adriana Stan; Thien-Phuc Doan; Souhwan Jung; Wei Herng Choong; Philip Sperl; Konstantin Böttinger (CoRR, 2025)

Replay Attacks Against Audio Deepfake Detection. - Nicolas M. Müller; Piotr Kawa; Wei Herng Choong; Adriana Stan; Aditya Tirumala Bukkapatnam; Karla Pizzi; Alexander Wagner; Philip Sperl (CoRR, 2025)