IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v241y2024ics0951832023006130.html
   My bibliography  Save this article

Dynamic probabilistic risk assessment for electric grid cybersecurity

Author

Listed:
  • Diao, Xiaoxu
  • Zhao, Yunfei
  • Smidts, Carol
  • Vaddi, Pavan Kumar
  • Li, Ruixuan
  • Lei, Hangtian
  • Chakhchoukh, Yacine
  • Johnson, Brian
  • Blanc, Katya Le

Abstract

Electric grid cybersecurity risk has become a significant concern of industries and governments. This paper proposes a dynamic probabilistic risk assessment method for electric grid cybersecurity risk analysis. The proposed method helps reduce the reliance on expert judgment, capture a broad range of components and system dynamics, and model the interactions between various contributing entities (e.g., attacker, operator). In addition, the scenarios with multiple events, such as the occurrence of both cyberattacks and failures of physical components, the occurrence of both cyberattacks and operators’ (in)correct reactions, are considered and analyzed. For each cyberattack scenario, Monte Carlo simulations are used to obtain possible sequences of the system's evolution under study and then derive risk estimates. As an application of the proposed method, the risk assessment method serves as the basis of risk-informed defense resource allocation to improve electric grid cybersecurity. The proposed method is verified using the IEEE 14-bus system by evaluating different security resource allocations for selected cyberattack scenarios.

Suggested Citation

  • Diao, Xiaoxu & Zhao, Yunfei & Smidts, Carol & Vaddi, Pavan Kumar & Li, Ruixuan & Lei, Hangtian & Chakhchoukh, Yacine & Johnson, Brian & Blanc, Katya Le, 2024. "Dynamic probabilistic risk assessment for electric grid cybersecurity," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
  • Handle: RePEc:eee:reensy:v:241:y:2024:i:c:s0951832023006130
    DOI: 10.1016/j.ress.2023.109699
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832023006130
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2023.109699?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ding, Zhetong & Chen, Chunyu & Cui, Mingjian & Bi, Wenjun & Chen, Yang & Li, Fangxing, 2021. "Dynamic game-based defensive primary frequency control system considering intelligent attackers," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    2. Zhao, Yunfei & Huang, Linan & Smidts, Carol & Zhu, Quanyan, 2020. "Finite-horizon semi-Markov game for time-sensitive attack response and probabilistic risk assessment in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    3. Babaleye, Ahmed O. & Kurt, Rafet Emek & Khan, Faisal, 2019. "Safety analysis of plugging and abandonment of oil and gas wells in uncertain conditions with limited data," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 133-141.
    4. Seppo Borenius & Pavithra Gopalakrishnan & Lina Bertling Tjernberg & Raimo Kantola, 2022. "Expert-Guided Security Risk Assessment of Evolving Power Grids," Energies, MDPI, vol. 15(9), pages 1-25, April.
    5. Antonello, Federico & Buongiorno, Jacopo & Zio, Enrico, 2022. "A methodology to perform dynamic risk assessment using system theory and modeling and simulation: Application to nuclear batteries," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    6. Andrew Fielder & Sandra König & Emmanouil Panaousis & Stefan Schauer & Stefan Rass, 2018. "Risk Assessment Uncertainties in Cybersecurity Investments," Games, MDPI, vol. 9(2), pages 1-14, June.
    7. Henneaux, Pierre & Labeau, Pierre-Etienne & Maun, Jean-Claude, 2012. "A level-1 probabilistic risk assessment to blackout hazard in transmission power systems," Reliability Engineering and System Safety, Elsevier, vol. 102(C), pages 41-52.
    8. Ding, Weiyong & Xu, Maochao & Huang, Yu & Zhao, Peng, 2020. "Cyber risks of PMU networks with observation errors: Assessment and mitigation," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    9. Wang, Wei & Cova, Gregorio & Zio, Enrico, 2022. "A clustering-based framework for searching vulnerabilities in the operation dynamics of Cyber-Physical Energy Systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    10. Zhang, Xi & Liu, Dong & Tu, Haicheng & Tse, Chi Kong, 2022. "An integrated modeling framework for cascading failure study and robustness assessment of cyber-coupled power grids," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    11. Ding, Weiyong & Xu, Maochao & Huang, Yu & Zhao, Peng & Song, Fengyi, 2021. "Cyber attacks on PMU placement in a smart grid: Characterization and optimization," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Berghout, Tarek & Benbouzid, Mohamed, 2022. "EL-NAHL: Exploring labels autoencoding in augmented hidden layers of feedforward neural networks for cybersecurity in smart grids," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    2. Badrsimaei, Hamed & Hooshmand, Rahmat-Allah & Nobakhtian, Soghra, 2023. "Observable placement of phasor measurement units for defense against data integrity attacks in real time power markets," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    3. Zhang, Xi & Liu, Dong & Tu, Haicheng & Tse, Chi Kong, 2022. "An integrated modeling framework for cascading failure study and robustness assessment of cyber-coupled power grids," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    4. Ding, Zhetong & Chen, Chunyu & Cui, Mingjian & Bi, Wenjun & Chen, Yang & Li, Fangxing, 2021. "Dynamic game-based defensive primary frequency control system considering intelligent attackers," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    5. Jianguo Ding & Attia Qammar & Zhimin Zhang & Ahmad Karim & Huansheng Ning, 2022. "Cyber Threats to Smart Grids: Review, Taxonomy, Potential Solutions, and Future Directions," Energies, MDPI, vol. 15(18), pages 1-37, September.
    6. Tang, Daogui & Fang, Yi-Ping & Zio, Enrico, 2023. "Vulnerability analysis of demand-response with renewable energy integration in smart grids to cyber attacks and online detection methods," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    7. Tang, Maochun & Xiahou, Tangfan & Liu, Yu, 2023. "Mission performance analysis of phased-mission systems with cross-phase competing failures," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    8. Liu, Hanchen & Wang, Chong & Ju, Ping & Li, Hongyu, 2022. "A sequentially preventive model enhancing power system resilience against extreme-weather-triggered failures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    9. Yijun Liu & Xiaokun Jin & Yunrui Zhang, 2024. "Identifying risks in temporal supernetworks: an IO-SuperPageRank algorithm," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-21, December.
    10. Zhao, Yixin & Cai, Baoping & Kang, Henry Hooi-Siang & Liu, Yiliu, 2023. "Cascading failure analysis of multistate loading dependent systems with application in an overloading piping network," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    11. Li, Weijun & Sun, Qiqi & Zhang, Jiwang & Zhang, Laibin, 2024. "Quantitative risk assessment of industrial hot work using Adaptive Bow Tie and Petri Nets," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    12. Juntao Chen & Quanyan Zhu & Tamer Başar, 2021. "Dynamic Contract Design for Systemic Cyber Risk Management of Interdependent Enterprise Networks," Dynamic Games and Applications, Springer, vol. 11(2), pages 294-325, June.
    13. Xie, Shuyi & Huang, Zimeng & Wu, Gang & Luo, Jinheng & Li, Lifeng & Ma, Weifeng & Wang, Bohong, 2024. "Combining precursor and Cloud Leaky noisy-OR logic gate Bayesian network for dynamic probability analysis of major accidents in the oil depots," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    14. Mostafa Shokry & Ali Ismail Awad & Mahmoud Khaled Abd-Ellah & Ashraf A. M. Khalaf, 2023. "When Security Risk Assessment Meets Advanced Metering Infrastructure: Identifying the Appropriate Method," Sustainability, MDPI, vol. 15(12), pages 1-17, June.
    15. Guo, Hengdao & Zheng, Ciyan & Iu, Herbert Ho-Ching & Fernando, Tyrone, 2017. "A critical review of cascading failure analysis and modeling of power system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 9-22.
    16. Xie, Haipeng & Tang, Lingfeng & Zhu, Hao & Cheng, Xiaofeng & Bie, Zhaohong, 2023. "Robustness assessment and enhancement of deep reinforcement learning-enabled load restoration for distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    17. Lilli, Giordano & Sanavia, Matteo & Oboe, Roberto & Vianello, Chiara & Manzolaro, Mattia & De Ruvo, Pasquale Luca & Andrighetto, Alberto, 2024. "A semi-quantitative risk assessment of remote handling operations on the SPES Front-End based on HAZOP-LOPA," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    18. Hunt, Kyle & Agarwal, Puneet & Zhuang, Jun, 2022. "On the adoption of new technology to enhance counterterrorism measures: An attacker–defender game with risk preferences," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    19. Li, Sheng & Liu, Wenwen & Wu, Ruizi & Li, Junli, 2023. "An adaptive attack model to network controllability," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    20. Fam, Mei Ling & He, Xuhong & Konovessis, Dimitrios & Ong, Lin Seng, 2020. "Using Dynamic Bayesian Belief Network for analysing well decommissioning failures and long-term monitoring of decommissioned wells," Reliability Engineering and System Safety, Elsevier, vol. 197(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:241:y:2024:i:c:s0951832023006130. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.