Trustworthy cyber-physical power systems using AI: dueling algorithms for PMU anomaly detection and cybersecurity

Energy systems require radical changes due to the conflicting needs of combating climate change and meeting rising energy demands. These revolutionary decentralization, decarbonization, and digitalization techniques have ushered in a new global energy paradigm. Waves of disruption have been felt acr...

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Published in:	The Artificial intelligence review Vol. 57; no. 7; p. 183
Main Authors:	Cali, Umit, Catak, Ferhat Ozgur, Halden, Ugur
Format:	Journal Article
Language:	English
Published:	Dordrecht Springer Netherlands 01.07.2024 Springer Springer Nature B.V
Subjects:	Algorithms Anomalies Artificial Intelligence Climate change Climatic changes Computer Science Credibility Critical infrastructure Cyber-physical systems Cybersecurity Cyberterrorism Data security Decentralization Digital technology Digitization Disruption Electric power systems Electric power transmission Electricity Electricity distribution Energy Energy industry Grammatical aspect Infrastructure International trade Internet Iterative methods Measurement Measuring instruments Mitigation Operators Phasors Power Security Trustworthiness
ISSN:	1573-7462, 0269-2821, 1573-7462
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Abstract	Energy systems require radical changes due to the conflicting needs of combating climate change and meeting rising energy demands. These revolutionary decentralization, decarbonization, and digitalization techniques have ushered in a new global energy paradigm. Waves of disruption have been felt across the electricity industry as the digitalization journey in this sector has converged with advances in artificial intelligence (AI). However, there are risks involved. As AI becomes more established, new security threats have emerged. Among the most important is the cyber-physical protection of critical infrastructure, such as the power grid. This article focuses on dueling AI algorithms designed to investigate the trustworthiness of power systems’ cyber-physical security under various scenarios using the phasor measurement units (PMU) use case. Particularly in PMU operations, the focus is on areas that manage sensitive data vital to power system operators’ activities. The initial stage deals with anomaly detection applied to energy systems and PMUs, while the subsequent stage examines adversarial attacks targeting AI models. At this stage, evaluations of the Madry attack, basic iterative method (BIM), momentum iterative method (MIM), and projected gradient descend (PGD) are carried out, which are all powerful adversarial techniques that may compromise anomaly detection methods. The final stage addresses mitigation methods for AI-based cyberattacks. All these three stages represent various uses of AI and constitute the dueling AI algorithm convention that is conceptualised and demonstrated in this work. According to the findings of this study, it is essential to investigate the trade-off between the accuracy of AI-based anomaly detection models and their digital immutability against potential cyberphysical attacks in terms of trustworthiness for the critical infrastructure under consideration.
AbstractList	Energy systems require radical changes due to the conflicting needs of combating climate change and meeting rising energy demands. These revolutionary decentralization, decarbonization, and digitalization techniques have ushered in a new global energy paradigm. Waves of disruption have been felt across the electricity industry as the digitalization journey in this sector has converged with advances in artificial intelligence (AI). However, there are risks involved. As AI becomes more established, new security threats have emerged. Among the most important is the cyber-physical protection of critical infrastructure, such as the power grid. This article focuses on dueling AI algorithms designed to investigate the trustworthiness of power systems’ cyber-physical security under various scenarios using the phasor measurement units (PMU) use case. Particularly in PMU operations, the focus is on areas that manage sensitive data vital to power system operators’ activities. The initial stage deals with anomaly detection applied to energy systems and PMUs, while the subsequent stage examines adversarial attacks targeting AI models. At this stage, evaluations of the Madry attack, basic iterative method (BIM), momentum iterative method (MIM), and projected gradient descend (PGD) are carried out, which are all powerful adversarial techniques that may compromise anomaly detection methods. The final stage addresses mitigation methods for AI-based cyberattacks. All these three stages represent various uses of AI and constitute the dueling AI algorithm convention that is conceptualised and demonstrated in this work. According to the findings of this study, it is essential to investigate the trade-off between the accuracy of AI-based anomaly detection models and their digital immutability against potential cyberphysical attacks in terms of trustworthiness for the critical infrastructure under consideration.
ArticleNumber	183
Audience	Academic
Author	Halden, Ugur Cali, Umit Catak, Ferhat Ozgur
Author_xml	– sequence: 1 givenname: Umit surname: Cali fullname: Cali, Umit email: umit.cali@ntnu.no organization: School of Physics, Engineering and Technology, University of York, Department of Electric Energy, Norwegian University of Science and Technology – sequence: 2 givenname: Ferhat Ozgur surname: Catak fullname: Catak, Ferhat Ozgur organization: The Faculty of Science and Technology, Department of Electrical Engineering and Computer Science, University of Stavanger – sequence: 3 givenname: Ugur surname: Halden fullname: Halden, Ugur organization: Department of Electric Energy, Norwegian University of Science and Technology
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SubjectTerms	Algorithms Anomalies Artificial Intelligence Climate change Climatic changes Computer Science Credibility Critical infrastructure Cyber-physical systems Cybersecurity Cyberterrorism Data security Decentralization Digital technology Digitization Disruption Electric power systems Electric power transmission Electricity Electricity distribution Energy Energy industry Grammatical aspect Infrastructure International trade Internet Iterative methods Measurement Measuring instruments Mitigation Operators Phasors Power Security Trustworthiness
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Title	Trustworthy cyber-physical power systems using AI: dueling algorithms for PMU anomaly detection and cybersecurity
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