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A clustering-based framework for searching vulnerabilities in the operation dynamics of Cyber-Physical Energy Systems

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  • Wang, Wei
  • Cova, Gregorio
  • Zio, Enrico

Abstract

Being highly digitalized and interconnected through smart sensors in an advanced communication network, Cyber-Physical Energy Systems (CPESs) enhance the dynamic control under different operational conditions, but bring up concerns on cybersecurity failures due to deliberate cyber-attacks. In this study, we propose a clustering-based framework for searching the minimum combination of the most vulnerable communication channels (between sensors and the control center) that are susceptible to the operation dynamics of CPESs. We first adopt a mixed-integer linear programming (MILP) approach to select the extreme operational condition period clusters, taking into account the multiple sources of uncertainty influencing the system dynamic behavior. For each cluster, we inject undetectable false data vectors into different sets of communication channels, and test their effects on system functionalities by resorting to the Conditional Value-at-Risk (CVaR) measure. The minimum combination of vulnerabilities is identified, when its False Data Injection Attacks (FDIAs) start to deviate the system functionality from the normal range.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:reensy:v:222:y:2022:i:c:s0951832022000758
    DOI: 10.1016/j.ress.2022.108400
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    as
    1. Zhaojun Hao & Francesco Di Maio & Enrico Zio, 2021. "Multi-State Reliability Assessment Model of Base-Load Cyber-Physical Energy Systems (CPES) during Flexible Operation Considering the Aging of Cyber Components," Energies, MDPI, vol. 14(11), pages 1-18, June.
    2. Wang, Wei & Cammi, Antonio & Di Maio, Francesco & Lorenzi, Stefano & Zio, Enrico, 2018. "A Monte Carlo-based exploration framework for identifying components vulnerable to cyber threats in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 24-37.
    3. Zio, E., 2018. "The future of risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 176-190.
    4. Zhou, Jian & Huang, Ning & Coit, David W. & Felder, Frank A., 2018. "Combined effects of load dynamics and dependence clusters on cascading failures in network systems," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 116-126.
    5. Zio, Enrico & Aven, Terje, 2011. "Uncertainties in smart grids behavior and modeling: What are the risks and vulnerabilities? How to analyze them?," Energy Policy, Elsevier, vol. 39(10), pages 6308-6320, October.
    6. Mena, Rodrigo & Hennebel, Martin & Li, Yan-Fu & Zio, Enrico, 2016. "A multi-objective optimization framework for risk-controlled integration of renewable generation into electric power systems," Energy, Elsevier, vol. 106(C), pages 712-727.
    7. Chatterjee, Samrat & Thekdi, Shital, 2020. "An iterative learning and inference approach to managing dynamic cyber vulnerabilities of complex systems," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    8. Jasiūnas, Justinas & Lund, Peter D. & Mikkola, Jani, 2021. "Energy system resilience – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    9. Zhang, Chao & Xu, Xin & Dui, Hongyan, 2020. "Analysis of network cascading failure based on the cluster aggregation in cyber-physical systems," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    10. Yang, Shenhao & Chen, Weirong & Zhang, Xuexia & Yang, Weiqi, 2021. "A Graph-based Method for Vulnerability Analysis of Renewable Energy integrated Power Systems to Cascading Failures," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    11. Hain, Martin & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2018. "Managing renewable energy production risk," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 1-19.
    12. Ren, Hongbo & Zhou, Weisheng & Nakagami, Ken'ichi & Gao, Weijun & Wu, Qiong, 2010. "Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 87(12), pages 3642-3651, December.
    13. Jesus Beyza & Eduardo Garcia-Paricio & Jose M. Yusta, 2019. "Applying Complex Network Theory to the Vulnerability Assessment of Interdependent Energy Infrastructures," Energies, MDPI, vol. 12(3), pages 1-16, January.
    14. Woodard, Mark & Marashi, Koosha & Sedigh Sarvestani, Sahra & Hurson, Ali R., 2021. "Survivability evaluation and importance analysis for cyber–physical smart grids," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    15. Marashi, Koosha & Sarvestani, Sahra Sedigh & Hurson, Ali R., 2021. "Identification of interdependencies and prediction of fault propagation for cyber–physical systems," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    16. Peng, Hao & Liu, Can & Zhao, Dandan & Han, Jianmin, 2019. "Reliability analysis of CPS systems under different edge repairing strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 532(C).
    17. Sansavini, G. & Piccinelli, R. & Golea, L.R. & Zio, E., 2014. "A stochastic framework for uncertainty analysis in electric power transmission systems with wind generation," Renewable Energy, Elsevier, vol. 64(C), pages 71-81.
    18. Sergey V. Buldyrev & Roni Parshani & Gerald Paul & H. Eugene Stanley & Shlomo Havlin, 2010. "Catastrophic cascade of failures in interdependent networks," Nature, Nature, vol. 464(7291), pages 1025-1028, April.
    19. Han, Lin & Zhao, Xudong & Chen, Zhilong & Gong, Huadong & Hou, Benwei, 2021. "Assessing resilience of urban lifeline networks to intentional attacks," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    20. Gao, Xingle & Peng, Minfang & Tse, Chi K., 2021. "Impact of wind power uncertainty on cascading failure in cyber–physical power systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    21. Ouyang, Min, 2016. "Critical location identification and vulnerability analysis of interdependent infrastructure systems under spatially localized attacks," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 106-116.
    22. Zatti, Matteo & Gabba, Marco & Freschini, Marco & Rossi, Michele & Gambarotta, Agostino & Morini, Mirko & Martelli, Emanuele, 2019. "k-MILP: A novel clustering approach to select typical and extreme days for multi-energy systems design optimization," Energy, Elsevier, vol. 181(C), pages 1051-1063.
    23. Fazel Mohammadi, 2021. "Emerging Challenges in Smart Grid Cybersecurity Enhancement: A Review," Energies, MDPI, vol. 14(5), pages 1-9, March.
    24. Teichgraeber, Holger & Brandt, Adam R., 2019. "Clustering methods to find representative periods for the optimization of energy systems: An initial framework and comparison," Applied Energy, Elsevier, vol. 239(C), pages 1283-1293.
    25. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    26. Zang, Tianlei & Gao, Shibin & Liu, Baoxu & Huang, Tao & Wang, Tao & Wei, Xiaoguang, 2019. "Integrated fault propagation model based vulnerability assessment of the electrical cyber-physical system under cyber attacks," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 232-241.
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    Cited by:

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