collaborators

12 papers

cs.AI2026

Actual causality in fault trees

Georgiana Caltais, Milan Lopuhaä-Zwakenberg, Mariëlle Stoelinga

Fault trees are a widely used as effective risk models for complex systems, answering the question "what can go wrong?", especially through minimal cut set analysis. We study fault…

cs.SE2026

Ontology-Grounded Capability Interaction Graphs: From Knowledge Graphs to Fault Trees

Manzi Aimé Ntagengerwa, Georgiana Caltais, Mariëlle Stoelinga

The development of Cyber-Physical Systems (CPSs) is inherently multidisciplinary, involving expertise from domains such as software engineering, electrical engineering, and mechatr…

cs.PL2026

CPSLint: A Domain-Specific Language Providing Data Validation and Sanitisation for Industrial Cyber-Physical Systems

Uraz Odyurt, Ömer Sayilir, Mariëlle Stoelinga +1

Industrial cyber-physical systems generate vast amounts of semi-structured time-series data that require careful preprocessing before they can be effectively used for machine learn…

math.GM2026

Fuzzy Fault Trees: the Fast and the Formal

Thi Kim Nhung Dang, Benedikt Peterseim, Milan Lopuhaä-Zwakenberg +1

We provide a rigorous framework for handling uncertainty in quantitative fault tree analysis based on fuzzy theory. We show that any algorithm for fault tree unreliability analysis…

cs.CR2026

How hard can it be? Quantifying MITRE attack campaigns with attack trees and cATM logic

Stefano M. Nicoletti, Milan Lopuhaä-Zwakenberg, Mariëlle Stoelinga +2

The landscape of cyber threats grows more complex by the day. Advanced Persistent Threats carry out attack campaigns - e.g. operations Dream Job, Wocao, and WannaCry - against whic…

cs.OH2025

Fault Tree Synthesis from Knowledge Graphs

Manzi Aimé Ntagengerwa, Georgiana Caltais, Mariëlle Stoelinga

A truly effective diagnostic system provides system engineers with valuable insights into the behavior of their machines, leveraging a rich body of (often tacit) expertise. Much of…