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Browser Fingerprinting: How to Protect Machine Learning Models and Data with Differential Privacy?

, , , , , and . Electronic Communications of the EASST, (2021)

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Identification and Evaluation of KPIs in SDN via Simulation for Establishing Topology Classifications and Prediction Models. University of Würzburg, (January 2020)Demystifying User-based Active Learning for Network Monitoring Tasks, , , , and . 2nd Workshop on Machine Learning & Networking (MaLeNe) as part of NetSys'23, Potsdam, Germany, (September 2023)Moving Down the Stack: Performance Evaluation of Packet Processing Technologies for Stateful Firewalls, , , , , and . NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium, page 1--7. IEEE, (2023)Browser Fingerprinting: How to Protect Machine Learning Models and Data with Differential Privacy?, , , , , and . Electron. Commun. Eur. Assoc. Softw. Sci. Technol., (2022)ML-based Performance Prediction of SDN using Simulated Data from Real and Synthetic Networks., , , and . NOMS, page 1-7. IEEE, (2022)Simulative evaluation of KPIs in SDN for topology classification and performance prediction models, , and . 2020 16th International Conference on Network and Service Management (CNSM), page 1--9. IEEE, (2020)Demystifying user-based active learning for network monitoring tasks, , , , and . (2023)Moving Down the Stack: Performance Evaluation of Packet Processing Technologies for Stateful Firewalls., , , , , and . NOMS, page 1-7. IEEE, (2023)Extending the OpenFlow OMNeT++ Suite. University of Würzburg, (February 2019)Transformation of Descartes Modeling Language to Queueing Networks. University of Würzburg, Am Hubland, Informatikgebäude, 97074 Würzburg, Germany, Bachelor Thesis, (September 2016)