A Hybrid and Modular Integration Concept for Anomaly Detection in Industrial Control Systems

Effective anomaly detection is essential for realizing modern and secure industrial control systems. However, the direct integration of anomaly detection within such a system is complex due to the wide variety of hardware used, different communication protocols, and given industrial requirements. Many components of an industrial control system allow direct integration, while others are designed as closed systems or do not have the required performance. At the same time, the effective usage of available resources and the sustainable use of energy are more important than ever for modern industry. Therefore, in this paper, we present a modular and hybrid concept that enables the integration of efficient and effective anomaly detection while optimising the use of available resources under consideration of industrial requirements. Because of the modular and hybrid properties, many functionalities can be outsourced to the respective devices, and at the same time, additional hardware can be integrated where required. The resulting flexibility allows the seamless integration of complete anomaly detection into existing and legacy systems without the need for expensive centralised or cloud-based solutions. Through a detailed evaluation within an industrial unit, we demonstrate the performance and versatility of our concept.

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Publication Details

Journal
AI
Published
2025-04-27
DOI
https://doi.org/10.3390/ai6050091
Citations
3
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
Field-Weighted Citation Impact
7.44
Controls
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article

A Hybrid and Modular Integration Concept for Anomaly Detection in Industrial Control Systems

Christian Goetz, Bernhard G. Humm
3 citations
AI
Anomaly Detection Techniques and Applications
7.44
article

A Hybrid and Modular Integration Concept for Anomaly Detection in Industrial Control Systems

Christian Goetz, Bernhard G. Humm
article en
3 citations

Abstract

Effective anomaly detection is essential for realizing modern and secure industrial control systems. However, the direct integration of anomaly detection within such a system is complex due to the wide variety of hardware used, different communication protocols, and given industrial requirements. Many components of an industrial control system allow direct integration, while others are designed as closed systems or do not have the required performance. At the same time, the effective usage of available resources and the sustainable use of energy are more important than ever for modern industry. Therefore, in this paper, we present a modular and hybrid concept that enables the integration of efficient and effective anomaly detection while optimising the use of available resources under consideration of industrial requirements. Because of the modular and hybrid properties, many functionalities can be outsourced to the respective devices, and at the same time, additional hardware can be integrated where required. The resulting flexibility allows the seamless integration of complete anomaly detection into existing and legacy systems without the need for expensive centralised or cloud-based solutions. Through a detailed evaluation within an industrial unit, we demonstrate the performance and versatility of our concept.

AIVol. 6(5)
Darmstadt University of Applied Sciences (DE)
Openalex Percentile: Top 3%
Anomaly Detection Techniques and Applications
7.44
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