2 citations · 2 across the 2 of their papers we have counts for
5 papers
Online and Interactive Bayesian Inference Debugging
Nathanael Nussbaumer, Markus Böck, Jürgen Cito
Probabilistic programming is a rapidly developing programming paradigm which enables the formulation of Bayesian models as programs and the automation of posterior inference. It fa…
On the Surprising Efficacy of LLMs for Penetration-Testing
Andreas Happe, Jürgen Cito
This paper presents a critical examination of the surprising efficacy of Large Language Models (LLMs) in penetration testing. The paper thoroughly reviews the evolution of LLMs and…
The Road to Hybrid Quantum Programs: Characterizing the Evolution from Classical to Hybrid Quantum Software
Vincenzo De Maio, Ivona Brandic, Ewa Deelman +1
Quantum computing exhibits the unique capability to natively and efficiently encode various natural phenomena, promising theoretical speedups of several orders of magnitude. Howeve…
Benchmarking Practices in LLM-driven Offensive Security: Testbeds, Metrics, and Experiment Design
Andreas Happe, Jürgen Cito
Large Language Models (LLMs) have emerged as a powerful approach for driving offensive penetration-testing tooling. Due to the opaque nature of LLMs, empirical methods are typicall…
Can LLMs Hack Enterprise Networks? Autonomous Assumed Breach Penetration-Testing Active Directory Networks
Andreas Happe, Jürgen Cito
Enterprise penetration-testing is often limited by high operational costs and the scarcity of human expertise. This paper investigates the feasibility and effectiveness of using La…