Controller Cyber-Attack Detection and Isolation

This article deals with the cyber security of industrial control systems. Methods for detecting and isolating process faults and cyber-attacks, consisting of elementary actions named “cybernetic faults” that penetrate the control system and destructively affect its operation, are analysed. FDI fault...

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Main Authors: Anna Sztyber-Betley, Michał Syfert, Jan Maciej Kościelny, Zuzanna Górecka
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/23/5/2778
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author Anna Sztyber-Betley
Michał Syfert
Jan Maciej Kościelny
Zuzanna Górecka
author_facet Anna Sztyber-Betley
Michał Syfert
Jan Maciej Kościelny
Zuzanna Górecka
author_sort Anna Sztyber-Betley
collection DOAJ
description This article deals with the cyber security of industrial control systems. Methods for detecting and isolating process faults and cyber-attacks, consisting of elementary actions named “cybernetic faults” that penetrate the control system and destructively affect its operation, are analysed. FDI fault detection and isolation methods and the assessment of control loop performance methods developed in the automation community are used to diagnose these anomalies. An integration of both approaches is proposed, which consists of checking the correct functioning of the control algorithm based on its model and tracking changes in the values of selected control loop performance indicators to supervise the control circuit. A binary diagnostic matrix was used to isolate anomalies. The presented approach requires only standard operating data (process variable (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>P</mi><mi>V</mi></mrow></semantics></math></inline-formula>), setpoint (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>S</mi><mi>P</mi></mrow></semantics></math></inline-formula>), and control signal (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>C</mi><mi>V</mi></mrow></semantics></math></inline-formula>). The proposed concept was tested using the example of a control system for superheaters in a steam line of a power unit boiler. Cyber-attacks targeting other parts of the process were also included in the study to test the proposed approach’s applicability, effectiveness, and limitations and identify further research directions.
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spelling doaj.art-7d30d8f742564d7bbc3ee2056c1bca722023-11-17T08:39:34ZengMDPI AGSensors1424-82202023-03-01235277810.3390/s23052778Controller Cyber-Attack Detection and IsolationAnna Sztyber-Betley0Michał Syfert1Jan Maciej Kościelny2Zuzanna Górecka3Faculty of Mechatronics, Warsaw University of Technology, 00-661 Warsaw, PolandFaculty of Mechatronics, Warsaw University of Technology, 00-661 Warsaw, PolandFaculty of Mechatronics, Warsaw University of Technology, 00-661 Warsaw, PolandFaculty of Mechatronics, Warsaw University of Technology, 00-661 Warsaw, PolandThis article deals with the cyber security of industrial control systems. Methods for detecting and isolating process faults and cyber-attacks, consisting of elementary actions named “cybernetic faults” that penetrate the control system and destructively affect its operation, are analysed. FDI fault detection and isolation methods and the assessment of control loop performance methods developed in the automation community are used to diagnose these anomalies. An integration of both approaches is proposed, which consists of checking the correct functioning of the control algorithm based on its model and tracking changes in the values of selected control loop performance indicators to supervise the control circuit. A binary diagnostic matrix was used to isolate anomalies. The presented approach requires only standard operating data (process variable (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>P</mi><mi>V</mi></mrow></semantics></math></inline-formula>), setpoint (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>S</mi><mi>P</mi></mrow></semantics></math></inline-formula>), and control signal (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>C</mi><mi>V</mi></mrow></semantics></math></inline-formula>). The proposed concept was tested using the example of a control system for superheaters in a steam line of a power unit boiler. Cyber-attacks targeting other parts of the process were also included in the study to test the proposed approach’s applicability, effectiveness, and limitations and identify further research directions.https://www.mdpi.com/1424-8220/23/5/2778cybersecuritycyber-attackfault detectionfault isolationcontrol loop performanceneural networks
spellingShingle Anna Sztyber-Betley
Michał Syfert
Jan Maciej Kościelny
Zuzanna Górecka
Controller Cyber-Attack Detection and Isolation
Sensors
cybersecurity
cyber-attack
fault detection
fault isolation
control loop performance
neural networks
title Controller Cyber-Attack Detection and Isolation
title_full Controller Cyber-Attack Detection and Isolation
title_fullStr Controller Cyber-Attack Detection and Isolation
title_full_unstemmed Controller Cyber-Attack Detection and Isolation
title_short Controller Cyber-Attack Detection and Isolation
title_sort controller cyber attack detection and isolation
topic cybersecurity
cyber-attack
fault detection
fault isolation
control loop performance
neural networks
url https://www.mdpi.com/1424-8220/23/5/2778
work_keys_str_mv AT annasztyberbetley controllercyberattackdetectionandisolation
AT michałsyfert controllercyberattackdetectionandisolation
AT janmaciejkoscielny controllercyberattackdetectionandisolation
AT zuzannagorecka controllercyberattackdetectionandisolation