Digital Twin-based Intrusion Detection for Industrial Control Systems

• Digital twins have recently gained significant interest in simulation, optimization, and predictive maintenance of Industrial Control Systems (ICS). Recent studies discuss the possibility of using digital twins for intrusion detection in industrial systems. Accordingly, this study contributes to a digital twin-based security framework for industrial control systems, extending its capabilities for simulation of attacks and defense mechanisms. Four types of process-aware attack scenarios are implemented on a standalone open-source digital twin of an industrial filling plant: command injection, network Denial of Service (DoS), calculated measurement modification, and naive measurement modification. A stacked ensemble classifier is proposed as the real-time intrusion detection, based on the offline evaluation of eight supervised machine learning algorithms. The designed stacked model outperforms previous methods in terms of F1Score and accuracy, by combining the predictions of various algorithms, while it can detect and classify intrusions in near real-time (0.1 seconds). This study also discusses the practicality and benefits of the proposed digital twin-based security framework

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)

MEDICIN OCH HÄLSOVETENSKAP  -- Annan medicin och hälsovetenskap -- Gerontologi, medicinsk/hälsovetenskaplig inriktning (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Other Medical and Health Sciences -- Gerontology, specialising in Medical and Health Sciences (hsv//eng)

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)

Nyckelord

Digital Twin

Industrial Control Systems

Intrusion Detection Systems

Machine Learning

Stacked Ensemble Model

Denial-of-service attack

E-learning

Intrusion detection

Supervised learning

Ensemble models

Industrial systems

Intrusion-Detection

Machine-learning

Predictive maintenance

Security frameworks

Simulation optimization

Learning algorithms

Gerontology

specialising in Medical and Health Sciences

Gerontologi

medicinsk/hälsovetenskaplig inriktning

Publikations- och innehållstyp

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