A Detection Method Against Load Redistribution Attacks in the Interdependence of the Natural Gas Network and Power System Based on Entropy
The increasing integration of gas-fired units (GFU) and power-to-gas (P2G) technology has led to the interconnection of natural gas and electricity networks. However, the advanced information and communication equipment in these integrated electricity-gas energy systems give rise to cybersecurity co...
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2023-09-01
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| Series: | Advances in Engineering and Intelligence Systems |
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| Online Access: | https://aeis.bilijipub.com/article_180456_d37ab50b770977e2935787e08f70e8a9.pdf |
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| author | Yaoying Wang |
| author_facet | Yaoying Wang |
| author_sort | Yaoying Wang |
| collection | DOAJ |
| description | The increasing integration of gas-fired units (GFU) and power-to-gas (P2G) technology has led to the interconnection of natural gas and electricity networks. However, the advanced information and communication equipment in these integrated electricity-gas energy systems give rise to cybersecurity concerns. This research proposes an entropy-based load redistribution (LR) attack detection approach for such integrated networks. The objective is to simultaneously overload multiple electrical lines and gas pipelines using a bi-level LR attack model, while ensuring system security through a defense strategy. Instead of relying on deep learning algorithms, this study leverages entropy-based techniques for attack detection. In order to thoroughly investigate the attack space, an attack detector based on entropy is trained utilizing a combination of normal data and randomly generated LR attacks. The efficacy of the suggested methodology in mitigating the hazards linked to inaccurate data injection is substantiated via simulations conducted on a modified version of the IEEE 118-bus power system, which incorporates a 14-node gas system. The findings indicate that the detector based on entropy exhibits efficacy in detecting both stochastic and purposeful attacks, thereby augmenting the security of interconnected gas and electricity networks. |
| format | Article |
| id | doaj-art-046772e0e3804b2bbb69c6b05de256f2 |
| institution | Kabale University |
| issn | 2821-0263 |
| language | English |
| publishDate | 2023-09-01 |
| publisher | Bilijipub publisher |
| record_format | Article |
| series | Advances in Engineering and Intelligence Systems |
| spelling | doaj-art-046772e0e3804b2bbb69c6b05de256f22025-02-12T08:47:20ZengBilijipub publisherAdvances in Engineering and Intelligence Systems2821-02632023-09-0100203768810.22034/aeis.2023.409287.1115180456A Detection Method Against Load Redistribution Attacks in the Interdependence of the Natural Gas Network and Power System Based on EntropyYaoying Wang0School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, Shaanxi, 710072, ChinaThe increasing integration of gas-fired units (GFU) and power-to-gas (P2G) technology has led to the interconnection of natural gas and electricity networks. However, the advanced information and communication equipment in these integrated electricity-gas energy systems give rise to cybersecurity concerns. This research proposes an entropy-based load redistribution (LR) attack detection approach for such integrated networks. The objective is to simultaneously overload multiple electrical lines and gas pipelines using a bi-level LR attack model, while ensuring system security through a defense strategy. Instead of relying on deep learning algorithms, this study leverages entropy-based techniques for attack detection. In order to thoroughly investigate the attack space, an attack detector based on entropy is trained utilizing a combination of normal data and randomly generated LR attacks. The efficacy of the suggested methodology in mitigating the hazards linked to inaccurate data injection is substantiated via simulations conducted on a modified version of the IEEE 118-bus power system, which incorporates a 14-node gas system. The findings indicate that the detector based on entropy exhibits efficacy in detecting both stochastic and purposeful attacks, thereby augmenting the security of interconnected gas and electricity networks.https://aeis.bilijipub.com/article_180456_d37ab50b770977e2935787e08f70e8a9.pdfpower systemnatural gas systemfalse data injectionload redistribution attackattack detectioninterdependency |
| spellingShingle | Yaoying Wang A Detection Method Against Load Redistribution Attacks in the Interdependence of the Natural Gas Network and Power System Based on Entropy Advances in Engineering and Intelligence Systems power system natural gas system false data injection load redistribution attack attack detection interdependency |
| title | A Detection Method Against Load Redistribution Attacks in the Interdependence of the Natural Gas Network and Power System Based on Entropy |
| title_full | A Detection Method Against Load Redistribution Attacks in the Interdependence of the Natural Gas Network and Power System Based on Entropy |
| title_fullStr | A Detection Method Against Load Redistribution Attacks in the Interdependence of the Natural Gas Network and Power System Based on Entropy |
| title_full_unstemmed | A Detection Method Against Load Redistribution Attacks in the Interdependence of the Natural Gas Network and Power System Based on Entropy |
| title_short | A Detection Method Against Load Redistribution Attacks in the Interdependence of the Natural Gas Network and Power System Based on Entropy |
| title_sort | detection method against load redistribution attacks in the interdependence of the natural gas network and power system based on entropy |
| topic | power system natural gas system false data injection load redistribution attack attack detection interdependency |
| url | https://aeis.bilijipub.com/article_180456_d37ab50b770977e2935787e08f70e8a9.pdf |
| work_keys_str_mv | AT yaoyingwang adetectionmethodagainstloadredistributionattacksintheinterdependenceofthenaturalgasnetworkandpowersystembasedonentropy AT yaoyingwang detectionmethodagainstloadredistributionattacksintheinterdependenceofthenaturalgasnetworkandpowersystembasedonentropy |