On the combination of randomized thresholds and non-parametric boundaries to protect digital watermarks against sensitivity attacks. - Erwin Quiring; Pascal Schöttle (IH&MMSec, 2014)

Fragile sensor fingerprint camera identification. - Erwin Quiring; Matthias Kirchner (WIFS, 2015)

Privacy Threats through Ultrasonic Side Channels on Mobile Devices. - Daniel Arp; Erwin Quiring; Christian Wressnegger; Konrad Rieck (EuroS&P, 2017)

Fraternal Twins: Unifying Attacks on Machine Learning and Digital Watermarking. - Erwin Quiring; Daniel Arp; Konrad Rieck (CoRR, 2017)

Forgotten Siblings: Unifying Attacks on Machine Learning and Digital Watermarking. - Erwin Quiring; Daniel Arp; Konrad Rieck (EuroS&P, 2018)

Adversarial Machine Learning Against Digital Watermarking. - Erwin Quiring; Konrad Rieck (EUSIPCO, 2018)

Privacy-Enhanced Fraud Detection with Bloom Filters. - Daniel Arp; Erwin Quiring; Tammo Krueger; Stanimir Dragiev; Konrad Rieck (SecureComm (1), 2018)

On the Security and Applicability of Fragile Camera Fingerprints. - Erwin Quiring; Matthias Kirchner; Konrad Rieck (ESORICS (1), 2019)

Misleading Authorship Attribution of Source Code using Adversarial Learning. - Erwin Quiring; Alwin Maier; Konrad Rieck (USENIX Security Symposium, 2019)

Backdooring and Poisoning Neural Networks with Image-Scaling Attacks. - Erwin Quiring; Konrad Rieck (SP (Workshops), 2020)

Adversarial Preprocessing: Understanding and Preventing Image-Scaling Attacks in Machine Learning. - Erwin Quiring; David Klein 001; Daniel Arp; Martin Johns; Konrad Rieck (USENIX Security Symposium, 2020)

Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification. - Erwin Quiring; Lukas Pirch; Michael Reimsbach; Daniel Arp; Konrad Rieck (CoRR, 2020)

On the Security of Machine Learning Beyond the Feature Space. - Erwin Quiring (2021)

Misleading Deep-Fake Detection with GAN Fingerprints. - Vera Wesselkamp; Konrad Rieck; Daniel Arp; Erwin Quiring (SP (Workshops), 2022)

Dos and Don'ts of Machine Learning in Computer Security. - Daniel Arp; Erwin Quiring; Feargus Pendlebury; Alexander Warnecke; Fabio Pierazzi; Christian Wressnegger; Lorenzo Cavallaro; Konrad Rieck (USENIX Security Symposium, 2022)

On the Detection of Image-Scaling Attacks in Machine Learning. - Erwin Quiring; Andreas Müller 025; Konrad Rieck (ACSAC, 2023)

No more Reviewer #2: Subverting Automatic Paper-Reviewer Assignment using Adversarial Learning. - Thorsten Eisenhofer; Erwin Quiring; Jonas Möller; Doreen Riepel; Thorsten Holz; Konrad Rieck (USENIX Security Symposium, 2023)

Lessons Learned on Machine Learning for Computer Security. - Daniel Arp; Erwin Quiring; Feargus Pendlebury; Alexander Warnecke; Fabio Pierazzi; Christian Wressnegger; Lorenzo Cavallaro; Konrad Rieck (IEEE Secur. Priv., 2023)

AI-Generated Faces in the Real World: A Large-Scale Case Study of Twitter Profile Images. - Jonas Ricker; Dennis Assenmacher; Thorsten Holz; Asja Fischer; Erwin Quiring (RAID, 2024)

The Impact of Uniform Inputs on Activation Sparsity and Energy-Latency Attacks in Computer Vision. - Andreas Müller 025; Erwin Quiring (SP (Workshops), 2024)

I still know it's you! On Challenges in Anonymizing Source Code. - Micha Horlboge; Erwin Quiring; Roland Meyer 001; Konrad Rieck (Proc. Priv. Enhancing Technol., 2024)

Pitfalls in Machine Learning for Computer Security. - Daniel Arp; Erwin Quiring; Feargus Pendlebury; Alexander Warnecke; Fabio Pierazzi; Christian Wressnegger; Lorenzo Cavallaro; Konrad Rieck (Commun. ACM, 2024)

Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models. - Andreas Müller 025; Denis Lukovnikov; Jonas Thietke; Asja Fischer; Erwin Quiring (CVPR, 2025)

Towards A Correct Usage of Cryptography in Semantic Watermarks for Diffusion Models. - Jonas Thietke; Andreas Müller 025; Denis Lukovnikov; Asja Fischer; Erwin Quiring (CoRR, 2025)