Short Biography
 

I studied applied computer science at the DHBW Stuttgart Campus Horb (2015-2018) and the University Heidelberg (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 assistent 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: https://nextcloud.smachmeier.de/apps/appointments/pub/%2BvCGfx8CS4GQXQ%3D%3D/form

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

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

Lectures and Seminars

• Assistant at the IT-Security Lecture 1
• Assistant at the IT-Security Lecture 2
• Assistant at the IT-Security Seminar

Publications

• 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.