9 citations · 19 across the 4 of their papers we have counts for
6 papers
Toward Securing AI Agents Like Operating Systems
Lukas Pirch, Micha Horlboge, Patrick Großmann +4
Autonomous agents based on large language models (LLMs) are rapidly emerging as a general-purpose technology, with recent systems such as OpenClaw extending their capabilities thro…
LLM-based Vulnerability Discovery through the Lens of Code Metrics
Felix Weissberg, Lukas Pirch, Erik Imgrund +3
Large language models (LLMs) excel in many tasks of software engineering, yet progress in leveraging them for vulnerability discovery has stalled in recent years. To understand thi…
SoK: Where to Fuzz? Assessing Target Selection Methods in Directed Fuzzing
Felix Weissberg, Jonas Möller, Tom Ganz +6
A common paradigm for improving fuzzing performance is to focus on selected regions of a program rather than its entirety. While previous work has largely explored how these locati…
Manipulating Feature Visualizations with Gradient Slingshots
Dilyara Bareeva, Marina M. -C. Höhne, Alexander Warnecke +5
Feature Visualization (FV) is a widely used technique for interpreting concepts learned by Deep Neural Networks (DNNs), which synthesizes input patterns that maximally activate a g…
Machine Unlearning of Features and Labels
Alexander Warnecke, Lukas Pirch, Christian Wressnegger +1
Removing information from a machine learning model is a non-trivial task that requires to partially revert the training process. This task is unavoidable when sensitive data, such…
Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification
Erwin Quiring, Lukas Pirch, Michael Reimsbach +2
Machine learning-based systems for malware detection operate in a hostile environment. Consequently, adversaries will also target the learning system and use evasion attacks to byp…