Critical Boundary Index-based Preventive and Post-detection Defense Approach Against False Data Injection Attacks in Power Systems with Distributed Energy Resources

Masahiro Furukakoi; Akito Nakadomari; Akie Uehara; Paras Mandal; Mitsunaga Kinjo; Tomonobu Senjyu

doi:10.35833/MPCE.2025.000962

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Critical Boundary Index-based Preventive and Post-detection Defense Approach Against False Data Injection Attacks in Power Systems with Distributed Energy Resources

Original Paper | 更新时间：2026-09-28

- Critical Boundary Index-based Preventive and Post-detection Defense Approach Against False Data Injection Attacks in Power Systems with Distributed Energy Resources
- Critical Boundary Index-based Preventive and Post-detection Defense Approach Against False Data Injection Attacks in Power Systems with Distributed Energy Resources
- MPCE 2026年14卷第5期页码：1744-1755
- 作者机构：
  
  1.Sanyo-Onoda City University, Yamaguchi 756-0884, Japan
  2.Saitama University, Saitama 338-8570, Japan
  3.University of the Ryukyus, Okinawa 903-0213, Japan
  4.The University of Texas at El Paso, El Paso, USA
- 作者简介：
  
  Masahiro Furukakoi
  Akito Nakadomari received the B.S., M.S., and Ph.D. degrees from the University of the Ryukyus, Okinawa, Japan, in 2020, 2022, and 2024, respectively. In 2024, he joined Saitama University, Saitama, Japan, where he is currently an Assistant Professor. His research interests include power system optimization and energy management. Email:nakadomari@mail.saitama-u.ac.jp
  Akie Uehara received the B.S., M.S., and Ph.D. degrees in electrical and electronics engineering from the University of the Ryukyus, Okinawa, Japan, in 2009, 2011, and 2013, respectively. In 2011, she joined the Okinawa Electric Power Company, Inc., Okinawa, Japan, and in 2025, she joined the University of the Ryukyus, where she is currently an Assistant Professor. Her current research interests include wind power generation system, power system, and energy management. Email: Email:uehara_a@cs.u-ryukyu.ac.jp
  Paras Mandal received the Ph.D. degree in electrical engineering from the University of the Ryukyus, Okinawa, Japan, in 2005. He is currently the Director of the Power and Renewable Energy Systems (PRES) Laboratory and a Professor of electrical and computer engineering with The University of Texas at El Paso, El Paso, USA. His current research interests include electrified transportation, application of artifical intelligence and machine learning to power system, forecasting, electricity market operation, and data-driven algorithm for cyber-physical system. Email:pmandal@utep.edu
  Mitsunaga Kinjo received the B.E. degree in electrical and information engineering from the University of the Ryukyus, Okinawa, Japan, in 1996, and the M.E. degree in electrical engineering and the Ph.D. degree in information science from Tohoku University, Sendai, Japan, in 1998 and 2001, respectively. From 2001 to 2003, he was a Researcher in the PRESTO program of the Japan Science and Technology Corporation (JST) conducted by Dr. Shigeo Sato at Tohoku University. From 2003 to 2006, he was a Research Fellow of the Research Institute of Electrical Communication (RIEC), Tohoku University. In 2006, he joined the University of the Ryukyus, where he is currently an Associate Professor. His research interests include neuromorphic computing, quantum computation algorithm, and their hardware implementation and application to combinatorial optimization problem. Email:mitsu18@tec.u-ryukyu.ac.jp
  Tomonobu Senjyu received the B.S. and M.S. degrees in electrical engineering from the University of the Ryukyus, Okinawa, Japan, in 1986 and 1988, respectively, and the Ph.D. degree in electrical engineering from Nagoya University, Nagoya, Japan, in 1994. He is currently a Full Professor with the Department of Electrical and Electronic Engineering, University of the Ryukyus. He is currently serving as a Member for the Science Council of Japan. He is an IEEJ Fellow and AAIA Fellow. His research interests include renewable energy, power system optimization and operation, power electronics, and advanced control of electrical machine. Email:b985542@tec.u-ryukyu.ac.jp
- 基金信息：
- DOI：10.35833/MPCE.2025.000962
  中图分类号：
- 收稿：2025-10-08，
  
  修回：2026-01-21，
  
  录用：2026-03-26，
  
  网络首发：2026-06-08，
  
  纸质出版：2026-09-15
- 稿件说明：
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Masahiro Furukakoi, Akito Nakadomari, Akie Uehara, 等. Critical Boundary Index-based Preventive and Post-detection Defense Approach Against False Data Injection Attacks in Power Systems with Distributed Energy Resources[J]. MPCE, 2026,14(5):1744-1755.

Furukakoi Masahiro,Nakadomari Akito,Uehara Akie,et al.Critical Boundary Index-based Preventive and Post-detection Defense Approach Against False Data Injection Attacks in Power Systems with Distributed Energy Resources[J].Journal of Modern Power Systems and Clean Energy,2026,14(05):1744-1755.
Masahiro Furukakoi, Akito Nakadomari, Akie Uehara, 等. Critical Boundary Index-based Preventive and Post-detection Defense Approach Against False Data Injection Attacks in Power Systems with Distributed Energy Resources[J]. MPCE, 2026,14(5):1744-1755. DOI： 10.35833/MPCE.2025.000962.

Furukakoi Masahiro,Nakadomari Akito,Uehara Akie,et al.Critical Boundary Index-based Preventive and Post-detection Defense Approach Against False Data Injection Attacks in Power Systems with Distributed Energy Resources[J].Journal of Modern Power Systems and Clean Energy,2026,14(05):1744-1755. DOI： 10.35833/MPCE.2025.000962.

摘要

Abstract

Cybersecurity in power systems with distributed energy resources (DERs) has become a serious challenge. This paper proposes a critical boundary index (CBI)-based preventive and post-detection defense approach against false data injection attacks (FDIAs) in power systems with DERs. The proposed approach utilizes the inherent attack resistance of CBI

a voltage stability index previously developed by the authors

to both preventively limit the impact of attacks and provide high-sensitivity post-attack detection of data manipulation. This paper quantitatively evaluates voltage stability monitoring approaches against FDIAs

comparing the resilience of CBI with conventional indices. Verification is conducted using IEEE 5-bus and 118-bus test systems with two types of FDIA scenarios: detection-avoidance type and misdirection type. The results demonstrate that when CBI is employed for monitoring

the achievable false data injection by attackers aiming to cause voltage drops is significantly reduced compared with conventional indices

maintaining system voltage within stable ranges. Additionally

CBI shows 1.5-2 times higher detection sensitivity compared with conventional indices. Notably

CBI demonstrates effective detection capability even against sophisticated attacks that falsely show improvement in voltage stability indices

which are difficult to detect using conventional approaches. These results confirm that the proposed approach effectively constrains attacker capabilities while providing enhanced detection sensitivity. Based on these findings

the proposed approach is shown to provide high sensitivity to even minor data tampering

offering a multi-layered defense combining prevention and detection for power systems with DERs.

关键词

Keywords

references

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