Katharina Dietz M. Sc.

• Moving Down the Stack: Performance Evaluation of Packet Processing Technologies for Stateful Firewalls Dietz, Katharina; Gray, Nicholas; Wolz, Manuel; Lorenz, Claas; Hoßfeld, Tobias; Seufert, Michael in 34th IEEE/IFIP Network Operations and Management Symposium (NOMS) (2023).
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  @inproceedings{info3-inproceedings-2023-2, address = {Miami, Florida}, author = {Dietz, Katharina and Gray, Nicholas and Wolz, Manuel and Lorenz, Claas and Hoßfeld, Tobias and Seufert, Michael}, booktitle = {34th IEEE/IFIP Network Operations and Management Symposium (NOMS)}, keywords = {ucn}, month = 5, title = {Moving Down the Stack: Performance Evaluation of Packet Processing Technologies for Stateful Firewalls}, year = 2023 }

  %0 Conference Paper %1 info3-inproceedings-2023-2 %A Dietz, Katharina %A Gray, Nicholas %A Wolz, Manuel %A Lorenz, Claas %A Hoßfeld, Tobias %A Seufert, Michael %B 34th IEEE/IFIP Network Operations and Management Symposium (NOMS) %C Miami, Florida %D 2023 %T Moving Down the Stack: Performance Evaluation of Packet Processing Technologies for Stateful Firewalls

• Comparing Traditional and GAN-based Approaches for the Synthesis of Wide Area Network Topologies Dietz, Katharina; Seufert, Michael; Hoßfeld, Tobias in 18th International Conference on Network and Service Management (CNSM) (2022).
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  @inproceedings{info3-inproceedings-2022-16, address = {Thessaloniki, Greece}, author = {Dietz, Katharina and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {18th International Conference on Network and Service Management (CNSM)}, keywords = {ucn}, month = 10, title = {Comparing Traditional and GAN-based Approaches for the Synthesis of Wide Area Network Topologies}, year = 2022 }

  %0 Conference Paper %1 info3-inproceedings-2022-16 %A Dietz, Katharina %A Seufert, Michael %A Hoßfeld, Tobias %B 18th International Conference on Network and Service Management (CNSM) %C Thessaloniki, Greece %D 2022 %T Comparing Traditional and GAN-based Approaches for the Synthesis of Wide Area Network Topologies
• ML-based Performance Prediction of SDN using Simulated Data from Real and Synthetic Networks Dietz, Katharina; Gray, Nicholas; Seufert, Michael; Hoßfeld, Tobias in 33th IEEE/IFIP Network Operations and Management Symposium (NOMS) (2022).
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  @inproceedings{info3-inproceedings-2022-2, address = {Budapest, Hungary}, author = {Dietz, Katharina and Gray, Nicholas and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {33th IEEE/IFIP Network Operations and Management Symposium (NOMS)}, keywords = {ucn}, month = 4, title = {ML-based Performance Prediction of SDN using Simulated Data from Real and Synthetic Networks}, year = 2022 }

  %0 Conference Paper %1 info3-inproceedings-2022-2 %A Dietz, Katharina %A Gray, Nicholas %A Seufert, Michael %A Hoßfeld, Tobias %B 33th IEEE/IFIP Network Operations and Management Symposium (NOMS) %C Budapest, Hungary %D 2022 %T ML-based Performance Prediction of SDN using Simulated Data from Real and Synthetic Networks

• Browser Fingerprinting: How to Protect Machine Learning Models and Data with Differential Privacy? Dietz, Katharina; Mühlhauser, Michael; Seufert, Michael; Gray, Nicholas; Hoßfeld, Tobias; Herrmann, Dominik in 1st International Workshop on Machine Learning in Networking (MaLeNe) (2021).
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  @inproceedings{info3-inproceedings-2021-16, address = {Lübeck, Germany (Virtual Conference)}, author = {Dietz, Katharina and Mühlhauser, Michael and Seufert, Michael and Gray, Nicholas and Hoßfeld, Tobias and Herrmann, Dominik}, booktitle = {1st International Workshop on Machine Learning in Networking (MaLeNe)}, keywords = {ucn}, month = 9, title = {Browser Fingerprinting: How to Protect Machine Learning Models and Data with Differential Privacy?}, year = 2021 }

  %0 Conference Paper %1 info3-inproceedings-2021-16 %A Dietz, Katharina %A Mühlhauser, Michael %A Seufert, Michael %A Gray, Nicholas %A Hoßfeld, Tobias %A Herrmann, Dominik %B 1st International Workshop on Machine Learning in Networking (MaLeNe) %C Lübeck, Germany (Virtual Conference) %D 2021 %T Browser Fingerprinting: How to Protect Machine Learning Models and Data with Differential Privacy?
• High Performance Network Metadata Extraction Using P4 for ML-Based Intrusion Detection Systems Gray, Nicholas; Dietz, Katharina; Seufert, Michael; Hoßfeld, Tobias in 22nd International Conference on High Performance Switching and Routing (HPSR) (2021).
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  @inproceedings{info3-inproceedings-2021-8, address = {Paris, France (Virtual Conference)}, author = {Gray, Nicholas and Dietz, Katharina and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {22nd International Conference on High Performance Switching and Routing (HPSR)}, keywords = {ucn}, month = 6, title = {High Performance Network Metadata Extraction Using P4 for ML-Based Intrusion Detection Systems}, year = 2021 }

  %0 Conference Paper %1 info3-inproceedings-2021-8 %A Gray, Nicholas %A Dietz, Katharina %A Seufert, Michael %A Hoßfeld, Tobias %B 22nd International Conference on High Performance Switching and Routing (HPSR) %C Paris, France (Virtual Conference) %D 2021 %T High Performance Network Metadata Extraction Using P4 for ML-Based Intrusion Detection Systems

• Identification and Evaluation of KPIs in SDN via Simulation for Establishing Topology Classifications and Prediction Models Dietz, Katharina PhD thesis, University of Würzburg. (2020, January).
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  @mastersthesis{info3-master-2020-14, author = {Dietz, Katharina}, keywords = {sys:hidden:completed}, month = 1, school = {University of Würzburg}, title = {Identification and Evaluation of KPIs in SDN via Simulation for Establishing Topology Classifications and Prediction Models}, year = 2020 }

  %0 Thesis %1 info3-master-2020-14 %A Dietz, Katharina %D 2020 %T Identification and Evaluation of KPIs in SDN via Simulation for Establishing Topology Classifications and Prediction Models
• Simulative Evaluation of KPIs in SDN for Topology Classification and Performance Prediction Models Gray, Nicholas; Dietz, Katharina; Hoßfeld, Tobias in 2020 16th International Conference on Network and Service Management (CNSM) (2020).
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  In recent years Software-defined Networking (SDN) has gained increased popularity by reducing the complexity of management operations and increasing the performance of networks. As a result, the number of purchasable SDN devices and their deployment in real world network constantly rises, making a thorough understanding of their behaviors and interactions even more important. In this work we analyze distributed controller architectures via simulation, identify Key Performance Indicators (KPIs), classify various network topologies with respect to their impact on SDN, as well as create a prediction model to estimate the overall performance of the overall SDN ecosystem, which can be used for network planning.

  @inproceedings{info3-inproceedings-2020-15, abstract = {In recent years Software-defined Networking (SDN) has gained increased popularity by reducing the complexity of management operations and increasing the performance of networks. As a result, the number of purchasable SDN devices and their deployment in real world network constantly rises, making a thorough understanding of their behaviors and interactions even more important. In this work we analyze distributed controller architectures via simulation, identify Key Performance Indicators (KPIs), classify various network topologies with respect to their impact on SDN, as well as create a prediction model to estimate the overall performance of the overall SDN ecosystem, which can be used for network planning.}, author = {Gray, Nicholas and Dietz, Katharina and Hoßfeld, Tobias}, booktitle = {2020 16th International Conference on Network and Service Management (CNSM)}, keywords = {sys:hidden:inproceedings}, title = {Simulative Evaluation of KPIs in SDN for Topology Classification and Performance Prediction Models}, year = 2020 }

  %0 Conference Paper %1 info3-inproceedings-2020-15 %A Gray, Nicholas %A Dietz, Katharina %A Hoßfeld, Tobias %B 2020 16th International Conference on Network and Service Management (CNSM) %D 2020 %T Simulative Evaluation of KPIs in SDN for Topology Classification and Performance Prediction Models %X In recent years Software-defined Networking (SDN) has gained increased popularity by reducing the complexity of management operations and increasing the performance of networks. As a result, the number of purchasable SDN devices and their deployment in real world network constantly rises, making a thorough understanding of their behaviors and interactions even more important. In this work we analyze distributed controller architectures via simulation, identify Key Performance Indicators (KPIs), classify various network topologies with respect to their impact on SDN, as well as create a prediction model to estimate the overall performance of the overall SDN ecosystem, which can be used for network planning.

• Extending the OpenFlow OMNeT++ Suite Dietz, Katharina PhD thesis, University of Würzburg. (2019, February).
  • [ BibTeX ]
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  @mastersthesis{info3-praktikum-2019-20, author = {Dietz, Katharina}, keywords = {sys:hidden:completed}, month = 2, school = {University of Würzburg}, title = {Extending the OpenFlow OMNeT++ Suite}, year = 2019 }

  %0 Thesis %1 info3-praktikum-2019-20 %A Dietz, Katharina %D 2019 %T Extending the OpenFlow OMNeT++ Suite