TY - GEN
T1 - Alarm Flood Reduction in Critical Infrastructures - Research Roadmap & Preliminary Results
AU - Schönböck, Johannes
AU - Retschitzegger, Werner
AU - Schwinger, Wieland
AU - Kapsammer, Elisabeth
AU - Pröll, Birgit
AU - Graf, David
AU - Lechner, Marianne
N1 - Publisher Copyright:
© 2026 IEEE.
PY - 2025
Y1 - 2025
N2 - The constant flood of alarms triggered by operational technology (OT) used in critical infrastructures (CRITIS) such as energy or traffic systems poses a serious challenge to their safe and efficient operation. Operators must quickly recognize truly critical situations and make life-saving decisions. This task is made more difficult by typical characteristics of CRITIS, including the high heterogeneity of OT systems, their wide geographical distribution, decentralized nature, and continuous, partly unpredictable evolution. As a result, operators often have only an isolated view of individual OT components, without understanding their interdependencies, which prevents effective alarm reduction. This paper tackles the problem of alarm flood reduction based on interdependencies in CRITIS, as studied in our research project iReduce. We present a research roadmap that outlines a two-step approach to identify and represent OT interdependencies. This is supported by a domain-adaptable OT knowledge base for semantic representation and by provenance mechanisms to handle system evolution. We also report on the current implementation status and first evaluation results, focusing on the exploration of OT interdependencies as a key step towards intelligent alarm reduction.
AB - The constant flood of alarms triggered by operational technology (OT) used in critical infrastructures (CRITIS) such as energy or traffic systems poses a serious challenge to their safe and efficient operation. Operators must quickly recognize truly critical situations and make life-saving decisions. This task is made more difficult by typical characteristics of CRITIS, including the high heterogeneity of OT systems, their wide geographical distribution, decentralized nature, and continuous, partly unpredictable evolution. As a result, operators often have only an isolated view of individual OT components, without understanding their interdependencies, which prevents effective alarm reduction. This paper tackles the problem of alarm flood reduction based on interdependencies in CRITIS, as studied in our research project iReduce. We present a research roadmap that outlines a two-step approach to identify and represent OT interdependencies. This is supported by a domain-adaptable OT knowledge base for semantic representation and by provenance mechanisms to handle system evolution. We also report on the current implementation status and first evaluation results, focusing on the exploration of OT interdependencies as a key step towards intelligent alarm reduction.
KW - Alarm Log Mining
KW - Critical Infrastructures (CRITIS)
KW - Operational Technology (OT)
KW - OT Interdependencies
UR - https://www.scopus.com/pages/publications/105036639568
U2 - 10.1109/ICIIS69028.2026.11450785
DO - 10.1109/ICIIS69028.2026.11450785
M3 - Conference contribution
AN - SCOPUS:105036639568
T3 - ICIIS 2025 - Next-Gen Engineering for Industry 5.0: Innovating Intelligent Systems for Human Centric Future: Proceedings of 2025 IEEE 19th International Conference on Industrial and Information Systems
SP - 533
EP - 538
BT - ICIIS 2025 - Next-Gen Engineering for Industry 5.0
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th IEEE International Conference on Industrial and Information Systems, ICIIS 2025
Y2 - 16 January 2026 through 17 January 2026
ER -