Thesis
Co-supervised or Supervised:
Brendan Gerrit Laschke, Cryptographic Properties of Anonymous Credential Systems, FU Berlin 2023
Wiktoria Krawczyk, Implementing a simple deep learning neural network in C++ for federate learning for RIOT, FU Berlin 2023
Vishal Kumar Singh, Anomaly Detection using Spatio-Temporal Dynamic Graph Neural Networks, FU Berlin 2023
Michael Peter Hoffmann, Multilingual Hate Speech Detection on Social Media: Applying Transfer Learning Methods to Classify German, Italian and Spanish Posts, FU Berlin 2023
Alexander Apostolos Rademann, OAuth 2.0 damals und heute: Analyse sicherheitsrelevanter Eigenschaften durch Threat Modeling, FU Berlin 2023
Magdalena Betram, Towards a lattice-based signature scheme for privacy-preserving protocols, FU Berlin 2023
Tobias Schalau, A Contrastive Self-Supervised Learning Model for Network Intrusion Detection, FU Berlin 2023
Leon Dirmeier, Lösung von Delegierungsproblemen des Unternehmenskontos mittels Proxy-Re-Encryption, FU Berlin 2023
Yarmina Anna Meszaros, Taxonomy of Privacy Attacks in Machine Learning, FU Berlin 2023
Jonny Lam, Herausforderung bei der Integration von Zero Trust in bestehende Systeme und Prozesse einer traditionellen IT Sicherheitsarchitektur, FU Berlin 2023
Marisa Frizzi Nest, Exploration of checkpoints in the context of membership inference attacks, FU Berlin 2023
Ina Fendel, Group-based Membership Inference Attack against Machine Learning Models, FU Berlin 2023
Yussuf Mohammed Kassem, Distributed Deep Neuroevolution for Offloading in Multi-Access Cloud-Edge Computing Networks, FU Berlin 2023
Valentin Pickel, A Comprehensive Description of the Quantum HHL Algorithm and its Application in the Cryptanalysis of the AES, FU Berlin 2023
Paulin Deupmann, Untersuchung des quantencomputerresistenten kryptographischen Verfahren CRYSTALS-Kyber, FU Berlin 2022
Manar Zaboub, Signal Strength Prediction and Visualization in 5G networks, Fraunhofer Fokus & FU Berlin 2022
Di Wang, Evaluating and Adapting Existing Neural Network Watermarking Approaches to Online Learning Scenarios, FU Berlin 2021
Jannis Ihrig, Attacking Differentially Private CNNs Trained with PATE, FU Berlin 2021
Tim von Känel, Practical Evaluation of Neural Network Watermarking Approaches, FU Berlin 2021
Oussama Bouanani, The Inuence of Training Parameters and Architectural Choices on the Vulnerability of Neural Networks to Membership Inference Attacks, FU Berlin 2021
Daniel Sosnovchyk, Evaluating Privacy of Synthetic Data Through Metrics, FU Berlin 2021
Felix Peterka, Design von Abhörkodes mit Deep Learning, FU Berlin 2021
Cezary Tomasz Pilaszewicz, Optimization of the size of a quantum register for Shor’s algorithm, FU Berlin 2021
Adrian Miloradovic, Precomputional Improvement of Supersingular Isogeny Diffie-Hellman, FU Berlin 2021
Jan Benninger, Abhörkodes für Semantische Sicherheit, FU Berlin 2021
Jasper Seidensticker, Gitterbasierte Kryptoanalyse: Die Coppersmith Methode, FU Berlin 2021
Maximilian Weigand, Realization Of An eIDAS Validation Service, FU Berlin 2020