| 2024 | ECAI | Defending Our Privacy with Backdoors. | Dominik Hintersdorf, Lukas Struppek, Daniel Neider, Kristian Kersting |
| 2024 | ICLR | Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks. | Lukas Struppek, Dominik Hintersdorf, Kristian Kersting |
| 2024 | IJCAI | Exploiting Cultural Biases via Homoglyphs inText-to-Image Synthesis (Abstract Reprint). | Lukas Struppek, Dominik Hintersdorf, Felix Friedrich, Manuel Brack, Patrick Schramowski, Kristian Kersting |
| 2023 | ICCV | Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis. | Lukas Struppek, Dominik Hintersdorf, Kristian Kersting |
| 2023 | IJCNN | Sparsely-gated Mixture-of-Expert Layers for CNN Interpretability. | Svetlana Pavlitska, Christian Hubschneider, Lukas Struppek, J. Marius Zllner |
| 2023 | VECoS | Balancing Transparency and Risk: An Overview of the Security and Privacy Risks of Open-Source Machine Learning Models. | Dominik Hintersdorf, Lukas Struppek, Kristian Kersting |
| 2022 | ICML | Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks. | Lukas Struppek, Dominik Hintersdorf, Antonio De Almeida Correia, Antonia Adler, Kristian Kersting |
| 2022 | IJCAI | To Trust or Not To Trust Prediction Scores for Membership Inference Attacks. | Dominik Hintersdorf, Lukas Struppek, Kristian Kersting |