Publications

Vera Wesselkamp, Konrad Rieck, Daniel Arp, Erwin Quiring (2022). Misleading Deep-Fake Detection with GAN Fingerprints. Deep Learning and Security Workshop (DLS).
DOI
Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck (2022). Dos and Don'ts of Machine Learning in Computer Security. Proc. of USENIX Security Symposium.
URL
Erwin Quiring, Konrad Rieck (2020). Backdooring and Poisoning Neural Networks with Image-Scaling Attacks. Deep Learning and Security Workshop (DLS).
DOI
Erwin Quiring, Lukas Pirch, Michael Reimsbach, Daniel Arp, Konrad Rieck (2020). Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification.
arXiv
Erwin Quiring, David Klein, Daniel Arp, Martin Johns, Konrad Rieck (2020). Adversarial Preprocessing: Understanding and Preventing Image-Scaling Attacks in Machine Learning. Proc. of USENIX Security Symposium.
URL
Erwin Quiring, Matthias Kirchner, Konrad Rieck (2019). On the Security and Applicability of Fragile Camera Fingerprints. Proc. of European Symposium on Research in Computer Security (ESORICS).
DOI
Erwin Quiring, Alwin Maier, Konrad Rieck (2019). Misleading Authorship Attribution of Source Code using Adversarial Learning. Proc. of USENIX Security Symposium.
URL
Daniel Arp and Erwin Quiring and Tammo Krueger and Stanimir Dragiev and Konrad Rieck (2018). Privacy-Enhanced Fraud Detection with Bloom Filters. Proc. of Int. Conference on Security and Privacy in Communication Networks (SECURECOMM).
DOI
Erwin Quiring, Daniel Arp, Konrad Rieck (2018). Forgotten Siblings: Unifying Attacks on Machine Learning and Digital Watermarking. Proc. of IEEE European Symposium on Security and Privacy (EuroS&P).
DOI
Erwin Quiring, Konrad Rieck (2018). Adversarial Machine Learning Against Digital Watermarking. European Signal Processing Conference (EUSIPCO).
DOI