M.Sc. Stefan Machmeier | |
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Phone: +49 6221 54 14537 Predoc | Office address/Post address Engineering Mathematics and Computing Lab (EMCL) |
Short Biography
I studied applied computer science at the DHBW Stuttgart Campus Horb (2015-2018) and the Heidelberg University (2020-2022). During my masters, I focused on cybersecurity with a master's thesis on "Honeypot Implementation in a Cloud environment". Additionally, I worked as a research assistant at bwInfoSec, where I have been a permanent team member since April 2022.
Research Interests
- Cybersecurity
- Explainability
- Machine Learning
Teaching
At University Heidelberg
If you are interested in IT security as part of an internship or thesis, you can contact me here
Supervisor of BA theses:
- Using Deep Packet Inspection to Analyse and Reduce DDoS Attacks on Servers and Applications
- Functionality and limitation of DPI circumvention software
- Analysing schemes for secure and memorable password generation
- Flow-based Traffic Classification Using Deep Vision
- Analyzing the BrakTooth family of experimental attacks on specific Bluetooth chipsets
- Vulnerabilities in Medical Data Transfer based on Blockchain Technologies
- DNS-Angriffe: Erkennung und Umgehung von Anomalieerkennungssystemen
- Reproducible Virtual Private Network Benchmarking using Declarative Environments
- Erkennung und Analyse von Shadowsocks-Traffic
- Validation of Public Proxy Servers using Internet-Wide-Scanning
- Advancing the Development of Training Environments for the Next Generation of Cybersecurity Specialists
Supervisor of MA theses:
- Adding Interpretability to an Anomaly-Based Method for Deep Packet Inspection in Intrusion Detection Systems
- Implementing an exploit as a Metasploit module and investigating the exploit ranking mechanism
- Schutz-Prinzipien für Softwarearchitekturen mit erhöhtem Schutzbedarf
- Passwortschemata zur Erstellung sicherer Passwörter allein durch Menschenhand
- Evaluation, benchmarking, and ensembling of Intrusion Detection Systems using a comparative platform
Lectures and Seminars
- Assistant at the IT-Security Lecture 1
- Assistant at the IT-Security Lecture 2
- Assistant at the IT-Security Seminar
- Assistant at the IT-Security Beginner Practicals
- Assistant at the IT-Security Advanced Practicals
Awards
- Best Paper Award: 2024 8th Cyber Security in Networking Conference (CSNet)
Publications
- M. Fuchs, S. Machmeier, S. Zelch, V. Heuveline, "A Reproducible VPN Benchmarking Framework for Comparison Across Implementations", In Proceedings of the 2025 14th International Conference on Software and Computer Applications (ICSCA '25).
- S. Machmeier, and V. Heuveline, "Detecting DNS Tunnelling and Data Exfiltration using Dynamic Time Warping", in 2024 8th Cyber Security in Networking Conference (CSNet), Paris, France, 2024.
- P. Memmesheimer, S. Machmeier, V. Heuveline, “Increasing Detection Rate for Imbalanced Malicious Traffic using Generative Adversarial Networks”, In Proceedings of the 2023 European Interdisciplinary Cybersecurity Conference (EICC '24).
- M. Schroeder, S. Machmeier, S. Maeng, V. Heuveline, "Validating CESU-8 Encoded Text Utilising SIMD Instructions", In Proceedings of the 2024 13th International Conference on Software and Computer Applications (ICSCA '24). https://doi.org/10.1145/3651781.3651797
- S. Machmeier, M. Hoecker, V. Heuveline, "Explainable Artificial Intelligence for Improving a Session-Based Malware Traffic Classification with Deep Learning", in 2023 IEEE Symposium Series on Computational Intelligence (SSCI), Mexico-City, Mexico, 2023. https://doi.org/10.1109/SSCI52147.2023.10371980
- S. Machmeier, M. Trageser, M. Buchwald, and V. Heuveline, "A generalizable approach for network flow image representation for deep learning", in 2023 7th Cyber Security in Networking Conference (CSNet), Montréal, Canada, 2023. https://doi.org/10.1109/CSNet59123.2023.10339761
- M. Schroeder, S. Machmeier, V. Heuveline (2023). Vtable hijacking: Object Type Integrity for run-time type information. Preprint Series of the EMCL.
- S. Machmeier (2023). Honeypot Implementation in a Cloud Environment. arXiv preprint arXiv:2301.00710.