Artur Leinweber

Artur is a researcher at the Institute for Internet Security at Westphalian University of Applied Sciences in Gelsenkirchen, Germany. His research interests include different approaches of machine learning especially artificial neural networks in the field of computer security, reverse engineering and ​automatic intrusion detection.

As part of the research team of the HypErSIS project, Artur is working on developing Virtual Machine Introspection (VMI) methods to automatically detect malware and attacks. To achieve this, Artur researches on machine learning based pattern recognition techniques to detect intrusions on VMI monitored computer systems.

Some of his prior works include the following:

• Beierlieb, L.; Schmitz, A.; Karazon, A.; Leinweber, A.; Dietrich, C. EPT Switching vs. Instruction Repair vs. Instruction Emulation: A Performance Comparison of Hyper-Breakpoint Variants. Eng 2025, 6, 278. PDF download. Published: 16 October 2025.
• Springer, R.; Schmitz, A.; Leinweber, A.; Urban, T.; Dietrich, C. Padding Matters – Exploring Function Detection in PE Files: Data/Toolset paper. 15th ACM Conference on Data and Application Security and Privacy (CODASPY ’25), June 2025.