Our Research
Our research group works on the application of machine learning in the computer security. In particular, we develop methods in the area of system security and application security, as for instance, attack detection or vulnerability discovery in software and embedded devices. Also, the robustness, security, and interpretability of machine learning methods are central to our research.
- Please find a full list of our publications here
- Information about current projects are available here
XAI Security
Explaining and understanding machine learning models is crucial for the reliable use of learning-based systems. In our research, we investigate the potentials and limits of XAI.
Web Measurements
Measurement studies are essential for web security research. We investigate the influence factors on the measurement of security phenomena and the impact on the drawn conclusions.
Security of AI
We research approaches to increase the robustness and the security of machine learning algrithms and AI. We analyze, harden, and refine ML models.
Malware Analysis
A thorough analysis of malware is essential for successfully protecting computer systems. In our research, we provide insights into novel threats and develop assitive tools using machine learning.
Learning-based Attack Detection
In our research, we also address the current urgent need of more advanced methods for detecting attacks. Machine learning and self-learning systems are particular promising tool to do so.
Vulnerability Discovery
Software vulnerabilities pose an inherent threat to the security of IT-systems. We develop learning-based methods to find such exploitable flaws before an adversary does.