On Cybersecurity Incident Response Decision Support System in Smart Grids

The growing complexity of control systems in smart grids has increased their vulnerability to cyber-attacks. In this paper, we introduce a modular decision support system to help system operators prioritize and select countermeasures following a cyber-incident. The proposed system combines attack graph analysis with multi-criteria decision-making techniques, enabling the evaluation of response actions based on customizable priorities such as cost, technical impact, and time required for deployment. Its architecture includes three independent components: a data management module, a decision-making engine, and a user interface, allowing integration of external knowledge bases and various decision strategies. The system is evaluated by analyzing its runtime behavior, optimization performance, and consistency with established cybersecurity standards and guidelines. Results show that the decision support system enhances operator capability in selecting effective countermeasures and provides a structured foundation for systematically comparing decision-making techniques in cyber-incident response for industrial control environments.

Authors

Institutions

Publication Details

Published
2025-09-29
DOI
https://doi.org/10.1109/smartgridcomm65349.2025.11204644
Primary Topic
Smart Grid and Power Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On Cybersecurity Incident Response Decision Support System in Smart Grids

Stefan Decker, Amirali Mahjoob, Andreas Ulbig, Ömer Sen et al.
Smart Grid and Power Systems
article

On Cybersecurity Incident Response Decision Support System in Smart Grids

Stefan Decker, Amirali Mahjoob, Andreas Ulbig, Ömer Sen, Martin Neumüller
article en

Abstract

The growing complexity of control systems in smart grids has increased their vulnerability to cyber-attacks. In this paper, we introduce a modular decision support system to help system operators prioritize and select countermeasures following a cyber-incident. The proposed system combines attack graph analysis with multi-criteria decision-making techniques, enabling the evaluation of response actions based on customizable priorities such as cost, technical impact, and time required for deployment. Its architecture includes three independent components: a data management module, a decision-making engine, and a user interface, allowing integration of external knowledge bases and various decision strategies. The system is evaluated by analyzing its runtime behavior, optimization performance, and consistency with established cybersecurity standards and guidelines. Results show that the decision support system enhances operator capability in selecting effective countermeasures and provides a structured foundation for systematically comparing decision-making techniques in cyber-incident response for industrial control environments.

RWTH Aachen University (DE)
Openalex Percentile: Top 70%
Smart Grid and Power Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.