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Katharina Dietz M. Sc.
| Telefon | (0931) 31-87343 (im Moment nicht besetzt, bitte per Mail melden) |
| katharina.dietz@informatik.uni-wuerzburg.de | |
| Raum | A212 |
Anschrift | Lehrstuhl für Informatik III |
Research Interests
Some of my research interests include the following:
- Everything related to network management, e.g., performance prediction or anomaly detection
- Machine Learning (ML) in communication networks, including but not limited to
- Data synthetization via Generative Adversarial Networks (GANs)
- Transfer Learning mechanisms
- Active Learning mechanisms
- Uncertainty in ML
- Network simulation with OMNeT++ and other tools
- Statistics evaluation and ML in R and Python
Open theses can be found here. Note that a lot of these topics can be tailored to either bachelor theses, master theses or student projects.
2023[ to top ]
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Moving Down the Stack: Performance Evaluation of Packet Processing Technologies for Stateful Firewalls in 34th IEEE/IFIP Network Operations and Management Symposium (NOMS) (2023).
2022[ to top ]
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Comparing Traditional and GAN-based Approaches for the Synthesis of Wide Area Network Topologies in 18th International Conference on Network and Service Management (CNSM) (2022).
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ML-based Performance Prediction of SDN using Simulated Data from Real and Synthetic Networks in 33th IEEE/IFIP Network Operations and Management Symposium (NOMS) (2022).
2021[ to top ]
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Browser Fingerprinting: How to Protect Machine Learning Models and Data with Differential Privacy? in 1st International Workshop on Machine Learning in Networking (MaLeNe) (2021).
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High Performance Network Metadata Extraction Using P4 for ML-Based Intrusion Detection Systems in 22nd International Conference on High Performance Switching and Routing (HPSR) (2021).
2020[ to top ]
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Identification and Evaluation of KPIs in SDN via Simulation for Establishing Topology Classifications and Prediction Models PhD thesis, University of Würzburg. (2020, January).
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Simulative Evaluation of KPIs in SDN for Topology Classification and Performance Prediction Models in 2020 16th International Conference on Network and Service Management (CNSM) (2020).
2019[ to top ]
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Extending the OpenFlow OMNeT++ Suite PhD thesis, University of Würzburg. (2019, February).
