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Optimizing Cyber Insurance and Defense for Multi-Energy Systems under False Data Injections

  • Alexis Pengfei Zhao
  • , Chenghong Gu
  • , Zhaoyao Bao
  • , Xi Cheng
  • , Mohannad Alhazmi
  • Cornell University
  • King Saud University

Research output: Contribution to journal › Article › peer-review

5   Link opens in a new tab Citations (SciVal)

Abstract

This article introduces a novel cyber insurance planning model specifically designed to enhance the resilience of information and communication technology (ICT)-integrated multi-energy systems (MES) against cyber threats, particularly false data injection (FDI) attacks. The proposed hierarchical cyber insurance planning model (HCIPM) offers an integrated approach to managing the dual challenges of financial risk and operational disruptions caused by sophisticated cyber-attacks. The model is built upon a two-stage hierarchical optimization framework: the first stage determines the optimal allocation of cyber insurance to minimize costs while ensuring adequate risk coverage, and the second stage focuses on real-time operational defense strategies, such as load shedding and resource management, to mitigate the impact of cyber incidents. A key innovation of the HCIPM is its incorporation of a distributionally robust optimization (DRO) methodology, combined with Conditional Value at Risk (CVaR), to effectively handle the uncertainties inherent in FDI attack scenarios. By representing extreme events and their probabilities, this framework ensures robust decision-making under high uncertainty. Extensive simulations conducted on a 33-20 node distribution system demonstrate the efficacy of the proposed model. Results indicate that the HCIPM achieves a 35% reduction in load shedding costs and a 28% improvement in resilience metrics, such as system recovery time and operational continuity, compared to traditional approaches. Additionally, the model demonstrates a significant decrease in financial losses attributable to cyber-attacks, with a 40% reduction in economic damages across high-risk scenarios. The findings underline the model's capability to not only reduce operational costs but also enhance system stability and resilience under diverse attack scenarios. By integrating financial mechanisms such as cyber insurance with technical defenses, the HCIPM represents a comprehensive solution for managing cyber risks in critical infrastructure. This research bridges the gap between operational resilience and financial protection, offering a pioneering framework for future applications of cyber insurance in power systems and other critical infrastructures. The proposed model provides a scalable and adaptable strategy, making it an invaluable tool for utilities and policymakers in their efforts to safeguard modern energy systems against evolving cyber threats.

Original languageEnglish
Article numbere70011
JournalIET Renewable Power Generation
Volume19
Issue number1
Early online date4 Mar 2025
DOIs
Publication statusE-pub ahead of print - 4 Mar 2025

Data Availability Statement

No datasets were generated or analyzed during the current study. Any relevant data generated during this research will be made available by the corresponding author upon reasonable request.

Funding

The authors would like to acknowledge the support provided by Researchers Supporting Project (Project Number: RSPD2025R635), King Saud University, Riyadh, Saudi Arabia. This work is in part supported by an EPSRC project: Supergen Energy Networks Impact Hub - EP/Y016114/2.

FundersFunder number
King Saud University
Engineering and Physical Sciences Research CouncilEP/Y016114/2

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • conditional value at risk (CVaR)
  • cyber insurance
  • distributionally robust optimization (DRO)
  • false data injection (FDI)
  • hierarchical optimization
  • multi-energy systems
  • system resilience

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment

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