Intern
Lehrstuhl für Informatik III

Katharina Dietz M. Sc.

Telefon (0931) 31-87343
E-Mail katharina.dietz@informatik.uni-wuerzburg.de
Raum A212

Anschrift

Lehrstuhl für Informatik III
Am Hubland
D-97074 Würzburg

Contents:  Overview | Working Group | Projects | Teaching | Publications

Research Interests

Some of my research interests include the following:

  • Everything related to network management, e.g., performance prediction or anomaly detection
  • Artificial Intelligence (AI) and Machine Learning (ML) in communication networks, including but not limited to
    • Data synthetization via Generative Adversarial Networks (GANs)
    • Usability and Explainability of AI/ML
    • Active Learning mechanisms
    • Uncertainty in AI/ML
  • Network simulation with OMNeT++ and other tools
  • Statistics evaluation and AI/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.

2024[ to top ]
  • 1.
    Dietz, K., Hajizadeh, M., Schleicher, J., Wehner, N., Geißler, S., Casas, P., Seufert, M., Hoßfeld, T.: Agree to Disagree: Exploring Consensus of XAI Methods for ML-based NIDS. In: 1st Workshop on Network Security Operations (NeSecOr) as part of CNSM’24. , Prague, Czech Republic (2024).
  • 1.
    Dietz, K., Hajizadeh, M., Wehner, N., Geißler, S., Casas, P., Seufert, M., Hoßfeld, T.: Certainly Uncertain: Demystifying ML Uncertainty for Active Learning in Network Monitoring Tasks. In: 20th International Conference on Network and Service Management (CNSM). , Prague, Czech Republic (2024).
  • 1.
    Dietz, K., Mühlhauser, M., Kögel, J., Schwinger, S., Sichermann, M., Seufert, M., Herrmann, D., Hoßfeld, T.: The Missing Link in Network Intrusion Detection: Taking AI/ML Research Efforts to Users. IEEE Access. (2024).
  • 1.
    Brandino, B., Grampin, E., Dietz, K., Wehner, N., Seufert, M., Hoßfeld, T., Casas, P.: HALIDS: a hardware-assisted machine learning IDS for in-network monitoring. In: 2024 8th Network Traffic Measurement and Analysis Conference (TMA), Dresden, Germany (2024).
  • 1.
    Seufert, M., Dietz, K., Wehner, N., Geißler, S., Schüler, J., Wolz, M., Hotho, A., Casas, P., Hoßfeld, T., Feldmann, A.: Marina: Realizing ML-Driven Real-Time Network Traffic Monitoring at Terabit Scale. Transactions on Network and Service Management (TNSM). (2024).
2023[ to top ]
  • 1.
    Dietz, K., Wehner, N., Casas, P., Hoßfeld, T., Seufert, M.: Demystifying User-based Active Learning for Network Monitoring Tasks. In: 2nd Workshop on Machine Learning & Networking (MaLeNe) as part of NetSys’23. , Potsdam, Germany (2023).
  • 1.
    Dietz, K., Seufert, M., Hoßfeld, T.: Want more WANs? Comparison of Traditional and GAN-based Generation of Wide Area Network Topologies via Graph and Performance Metrics. Transactions on Network and Service Management (TNSM). (2023).
  • 1.
    Dietz, K., Gray, N., Wolz, M., Lorenz, C., Hoßfeld, T., Seufert, M.: Moving Down the Stack: Performance Evaluation of Packet Processing Technologies for Stateful Firewalls. In: 34th IEEE/IFIP Network Operations and Management Symposium (NOMS). , Miami, Florida (2023).
2022[ to top ]
  • 1.
    Dietz, K., Seufert, M., Hoßfeld, T.: Comparing Traditional and GAN-based Approaches for the Synthesis of Wide Area Network Topologies. In: 18th International Conference on Network and Service Management (CNSM). , Thessaloniki, Greece (2022).
  • 1.
    Dietz, K., Gray, N., Seufert, M., Hoßfeld, T.: ML-based Performance Prediction of SDN using Simulated Data from Real and Synthetic Networks. In: 33th IEEE/IFIP Network Operations and Management Symposium (NOMS). , Budapest, Hungary (2022).
2021[ to top ]
  • 1.
    Dietz, K., Mühlhauser, M., Seufert, M., Gray, N., Hoßfeld, T., Herrmann, D.: Browser Fingerprinting: How to Protect Machine Learning Models and Data with Differential Privacy?. In: 1st International Workshop on Machine Learning in Networking (MaLeNe) as part of NetSys’21. , Lübeck, Germany (Virtual Conference) (2021).
  • 1.
    Gray, N., Dietz, K., Seufert, M., Hoßfeld, T.: High Performance Network Metadata Extraction Using P4 for ML-Based Intrusion Detection Systems. In: 22nd International Conference on High Performance Switching and Routing (HPSR). , Paris, France (Virtual Conference) (2021).
2020[ to top ]
  • 1.
    Dietz, K.: Identification and Evaluation of KPIs in SDN via Simulation for Establishing Topology Classifications and Prediction Models, (2020).
  • 1.
    Gray, N., Dietz, K., Hoßfeld, T.: 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 ]
  • 1.
    Dietz, K.: Extending the OpenFlow OMNeT++ Suite, (2019).