本文旨在評估多種非正確數據滲入攻擊對於電力系統所造成之線路流量變化影響，並以功率變動指標為核心方法進行線路流量快速計算。本研究考量電網資安風險，一旦攻擊者掌握部分或全部系統資訊，即可建構難以被偵測之非正確數據，進而誤導狀態估計與決策機制，造成線路過載與供電風險。因此，本文建構三種攻擊模式，分別為針對所有匯流排、特定匯流排以及特定攻擊區域進行非正確數據滲入，並以數學模型設計滲入條件，以模擬強化攻擊隱蔽性，接著應用功率變動指標進行評估非正確數據滲入後對於系統潮流的影響，並分別經由三種模擬系統進行測試。模擬結果顯示，攻擊策略可在不顯著改變總負載情況下，有效改變線路流量，甚至逼近其傳輸容量上限。本文所提方法可協助識別高風險區域，並提供預警與防護策略制定之依據，具有實務應用潛力，對於電網資安建構具有實務參考價值。

This study aims to evaluate the impact of various false data injection (FDI) attacks on line flow variations in power systems, utilizing the Power Variation Index (PVI) as the core method for rapid line flow computation. Considering the cybersecurity risks of modern power grids, once an attacker gains access to partial or complete system information, it becomes possible to construct undetectable false data that can mislead state estimation and decision-making processes, leading to line overloading and potential power supply risks. To assess the impact of this issue, the study establishes three types of attack models: injecting false data into all buses, specific buses, and designated attack regions. Mathematical models are also developed to define the injection conditions, enhancing the stealthiness of the attacks. The PVI method is then applied to assess the resulting changes in system power flows, and tests are conducted on three different simulation systems. Simulation results demonstrate that these attack strategies can effectively alter line flows without significantly changing the total system load, pushing power lines close to their transmission capacity limits. This proposed method helps identify high-risk areas and provides a basis for early warning and defense strategy development. It offers strong practical applicability and serves as a valuable reference for strengthening cybersecurity in power grid operations.

[1] J. Liu, Y. Xiao, S. Li, W. Liang, and C. L. P. Chen, “Cyber Security and Privacy Issues in Smart Grids,” IEEE Communications Surveys & Tutorials, vol. 14, no. 4, pp. 981-997, Fourth Quarter 2012.
[2] X. Fang, S. Misra, G. Xue, and D. Yang, “Smart Grid-The New and Improved Power Grid: A Survey,” IEEE Communications Surveys & Tutorials, vol. 14, no. 4, pp. 994-980, Oct. 2012.
[3] A. S. Musleh, G. Chen, and Z. Y. Dong, “A Survey on the Detection Algorithms for False Data Injection Attacks in Smart Grids," IEEE Transactions on Smart Grid, vol. 11, no. 3, pp. 2218-2234, May 2020.
[4] Y. Liu, M. K. Reiter, and P. Ning, “False Data Injection Attacks Against State Estimation in Electric Power Grids,” Proceedings 16th ACM Conference Computation and Communication Security, Chicago, Illinois, USA, pp. 21-32, Nov. 2009.
[5] R. Deng, P. Zhuang, and H. Liang, “False Data Injection Attacks Against State Estimation in Power Distribution Systems,” IEEE Transactions on Smart Grid, vol. 10, no. 3, pp. 2871-2881, May 2019.
[6] P. Verma and C. Chakraborty, “High Impact Local Load Redistribution Attack Without Confidential Network Information,” IEEE Transactions on Smart Grid, vol. 15, no. 2, pp. 2383-2386, Mar. 2024.
[7] Y. Sun, W. -T. Li, W. Song, and C. Yuen, “False Data Injection Attacks with Local Topology Information Against Linear State Estimation,” 2015 IEEE Innovative Smart Grid Technologies, Bangkok, Thailand, pp. 1-5, Nov. 2015.
[8] Y. Yuan, Z. Li, and K. Ren, “Modeling Load Redistribution Attacks in Power Systems,” IEEE Transactions on Smart Grid, vol. 2, no. 2, pp. 382–390, Jun. 2011.
[9] X. Liu, Z. Li, Z. Shuai, and Y. Wen, “Cyber Attacks Against the Economic Operation of Power Systems: A fast solution,” IEEE Transactions on Smart Grid, vol. 8, no. 2, pp. 1023-1025, Mar. 2017.
[10] Y. Yuan, Z. Li, and K. Ren, “Quantitative Analysis of Load Redistribution Attacks in Power Systems,” IEEE Transactions on Parallel Distribution System, vol. 23, no. 9, pp. 1731-1738, Sept. 2012.
[11] Y. Tan, Y. Li, Y. Cao, and M. Shahidehpour, “Cyber-Attack on Overloading Multiple Lines: A Bilevel Mixed-integer Linear Programming Model,” IEEE Transactions on Smart Grid, vol. 9, no. 2, pp. 1534-1536, Mar. 2018.
[12] Y. Liu, S. Gao, J. Shi, X. Wei, and Z. Han, “Sequential-Mining-Based Vulnerable Branches Identification for the Transmission Network Under Continuous Load Redistribution Attacks,” IEEE Transactions on Smart Grid, vol. 11, no. 6, pp. 5151-5160, Nov. 2020.
[13] D. K. Molzahn and J. Wang, “Detection and Characterization of Intrusions to Network Parameter Data in Electric Power Systems,” IEEE Transactions on Smart Grid, vol. 10, no. 4, pp. 3610-3618, July 2019.
[14] C. Liu, W. He, R. Deng, Y. -C. Tian, and W. Du, “False-Data-Injection-Enabled Network Parameter Modifications in Power Systems: Attack and Detection,” IEEE Transactions on Industrial Informatics, vol. 19, no. 1, pp. 177-188, Jan. 2023.
[15] X. Liu and Z. Li, “Local Topology Attacks in Smart Grids,” IEEE Transactions on Smart Grid, vol. 8, no. 6, pp. 2617-2626, Nov. 2017.
[16] R. Kaviani and K. W. Hedman, “An Enhanced Energy Management System Including a Real-Time Load-Redistribution Threat Analysis Tool and Cyber-Physical SCED,” IEEE Transactions on Power Systems, vol. 37, no. 5, pp. 3346-3358, Sept. 2022.
[17] T. C. Gulcu, V. Chatziafratis, Y. Zhang, and O. Yağan, “Attack Vulnerability of Power Systems Under an Equal Load Redistribution Model,” IEEE/ACM Transactions on Networking, vol. 26, no. 3, pp. 1306-1319, Jun. 2018.
[18] X. Liu, Z. Bao, D. Lu, and Z. Li, “Modeling of Local False Data Injection Attacks With Reduced Network Information,” IEEE Transactions on Smart Grid, vol. 6, no. 4, pp. 1-1, Jul. 2015.
[19] D. Şengül, E. Duymaz, and M. Göl, “Identification of Bad Solar Power Generation Data,” Signal Processing and Communications Applications Conference, Antalya, Turkey, pp. 1-4, May 2017.
[20] Z.-H. Yu and W.-L. Chin, “Blind False Data Injection Attack Using PCA Approximation Method in Smart Grid,” IEEE Transactions on Smart Grid, vol. 6, no. 3, pp. 1219–1226, May 2015.
[21] H. T. Reda, A. Mahmood, A. Anwar, and N. Chilamkurti, “Adversarial Models Towards Data Availability and Integrity of Distributed State Estimation for Industrial IoT-Based Smart Grid,” IEEE Transactions on Industrial Informatics, vol. 18, no. 6, pp. 3823-3833, Jun. 2022.
[22] N. N. Tran, H. R. Pota, Q. N. Tran, and J. Hu, “Designing Constraint-Based False Data Injection Attacks Against the Unbalanced Distribution Smart Grids,” IEEE Transactions on Smart Grid, vol. 11, no. 3, pp. 2345-2356, May. 2020.
[23] M. Ozay, I. Esnaola, F. T. Yarman Vural, S. R. Kulkarni, and H. V. Poor, “Sparse Attack Construction and State Estimation in the Smart Grid: Centralized and Distributed Models,” IEEE Transactions on Smart Grid, vol. 7, no. 1, pp. 1-10, Jan. 2016.
[24] B. Tang, J. Yan, S. Kay, and H. He, “Detection of False Data Injection Attacks in Smart Grid Under Colored Gaussian Noise,” IEEE Transactions on Smart Grid, vol. 9, no. 3, pp. 1-9, May 2018.
[25] N. N. Tran, H. R. Pota, Q. N. Tran, and J. Hu, “Designing Constraint-Based False Data Injection Attacks Against the Unbalanced Distribution Smart Grids,” IEEE Transactions on Smart Grid, vol. 11, no. 3, pp. 2345–2356, May 2020.
[26] M. Ozay, I. Esnaola, F. T. Yarman Vural, S. R. Kulkarni, and H. V. Poor, “Sparse Attack Construction and State Estimation in the Smart Grid: Centralized and Distributed Models,” IEEE Transactions on Smart Grid, vol. 7, no. 1, pp. 1-10, Jan. 2016.
[27] B. Tang, J. Yan, S. Kay, and H. He, “Detection of False Data Injection Attacks in Smart Grid Under Colored Gaussian Noise,” IEEE Transactions on Smart Grid, vol. 9, no. 3, pp. 1-9, May 2018.
[28] G. Hug and J. A. Giampapa, “Vulnerability Assessment of AC State Estimation with Respect to False Data Injection Cyber-Attacks,” IEEE Transactions on Smart Grid, vol. 3, no. 3, pp. 1362-1370, Sept. 2012.
[29] Y. Liu, P. Ning, and M. K. Reiter, “False Data Injection Attacks Against State Estimation in Electric Power Grids,” ACM Transactions on Information and System Security, vol. 14, no. 1, pp. 13:1-13:33, May 2011.
[30] G. Dán and H. Sandberg, “Stealth Attacks and Protection Schemes for State Estimators in Power Systems,” First IEEE International Conference on Smart Grid Communications, Gaithersburg, MD, USA, pp. 214-21, Oct. 2010.
[31] J. Liang, L. Sankar and O. Kosut, “Vulnerability Analysis and Consequences of False Data Injection Attack on Power System State Estimation,” IEEE Transactions on Power Systems, vol. 31, no. 5, pp. 3864-3872, Sep. 2016.
[32] V. Kekatos and G. B. Giannakis, “Distributed Robust Power System State Estimation,” IEEE Transactions on Power Systems, vol. 28, no. 2, pp. 1617-1626, May 2013.
[33] W. D. Stevenson, Elements of Power System Analysis, 4th ed. New York: McGraw-Hill, 1982.