Felix Morsbach

M. Sc. Felix Morsbach

About the Scientist

Felix Morsbach is a PhD student at the chair of Privacy and Security at KIT. He has a background in software engineering, embedded systems and high performance computing. His current research interest lies in privacy-preserving data analytics with a strong focus on privacy-preserving machine learning with differential privacy guarantees.

Research interests:

  • Privacy-Preserving Machine Learning
  • Membership Inference Attacks
  • Technical Privacy Notions (e.g. Differential Privacy)
  • Privacy Enhancing Technologies
  • Federated and Collaborative Learning

If you are a student at KIT and interested in writing your Bachelor or Master thesis in one of the topics above, please feel encouraged to contact me. I am always looking for motivated students.

Publications


BFId: Identity Inference Attacks Utilizing Beamforming Feedback Information
Todt, J.; Morsbach, F.; Strufe, T.
2025. Proceedings of 32nd ACM SIGSAC Conference on Computer and Communications Security (CCS ’25), Taipei, October 13–17, 2025, Association for Computing Machinery (ACM). doi:10.1145/3719027.3765062
Practitioner Motives to Use Different Hyperparameter Optimization Methods
Kannengiesser, N.; Hasebrook, N.; Morsbach, F.; Zöller, M.-A.; Franke, J. K. H.; Lindauer, M.; Hutter, F.; Sunyaev, A.
2025. ACM Transactions on Computer-Human Interaction. doi:10.1145/3745771
R+R: Understanding Hyperparameter Effects in DP-SGD
Morsbach, F.; Reubold, J. L.; Strufe, T.
2024. 40th Annual Computer Security Applications Conference (ACSAC), Honolulu, HI, USA, 09-13 December 2024, 1217–1230, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ACSAC63791.2024.00097
Human-Centered Design for Data-Sparse Tailored Privacy Information Provision
Goram, M.; Dehling, T.; Morsbach, F.; Sunyaev, A.
2023. Human Factors in Privacy Research. Ed.: N. Gerber, 283–298, Springer International Publishing. doi:10.1007/978-3-031-28643-8_14
Why Do Machine Learning Practitioners Still Use Manual Tuning? A Qualitative Study
Hasebrook, N.; Morsbach, F.; Kannengießer, N.; Zöller, M.; Franke, J.; Lindauer, M.; Hutter, F.; Sunyaev, A.
2022. Karlsruher Institut für Technologie (KIT). doi:10.48550/ARXIV.2203.01717
Architecture Matters: Investigating the Influence of Differential Privacy on Neural Network Design
Morsbach, F.; Dehling, T.; Sunyaev, A.
2021. Presented at NeurIPS 2021 Workshop on Privacy in Machine Learning (PriML 2021), 14.12.2021. doi:10.48550/arXiv.2111.14924
DecFL: An Ubiquitous Decentralized Model Training Protocol and Framework Empowered by Blockchain
Morsbach, F.; Toor, S.
2021. BSCI ’21: Proceedings of the 3rd ACM International Symposium on Blockchain and Secure Critical Infrastructure, 61–68, Association for Computing Machinery (ACM). doi:10.1145/3457337.3457842